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Intestinal dilatation syndrome (IDS) is a segmental enteropathy characterized by dilatation of the junction of the ileum and jejunum (Meckel's diverticulum). IDS severely affects the poultry industry by causing a chronic and irreversible drop in egg laying, reducing feed conversion efficiency, and increasing the mortality rate. The clinical and pathological features of IDS in white laying hens were described, and viral molecular and metagenomic research was conducted. The 50 – to 60-day-old chickens presented pale mucosa, apathy, depression, ruffled feathers, and diarrhoea, accompanied by a 20% loss in fertile egg production, 20% culling of birds, and 5% mortality. The main findings at necropsy were marked intestinal dilatation with intestinal stasis, a narrow distal jejunum in the region of Meckel's diverticulum, and undigested food. Microscopic analysis revealed marked atrophic lymphoplasmacytic and heterophilic enteritis with hyperplastic crypts, ulceration, and heterophilic and lymphoplasmacytic perineuritis. The molecular assays consistently detected the presence of chicken parvovirus in the three segments of the intestine, pancreas, and proventriculus, as well as chicken megrivirus in the intestinal contents. Marked atrophic enteritis with perineuritis and intestinal stasis were associated with clinical manifestations of poor intestinal absorption and secondary bacterial infection. Our data provide useful information about IDS and highlight the importance of further studies to determine the specific role of each detected virus in this syndrome. RESEARCH HIGHLIGHTS: 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. [ABSTRACT FROM AUTHOR]

Abstract The integration of next-generation sequencing into clinical diagnostics and surveillance initiatives is impeded by the lack of data analysis pipelines that align with privacy legislation and laboratory certification protocols. To address these challenges, we developed Jovian, an open-source, virus-focused, metagenomic analysis workflow for Illumina data. Jovian generates scaffolds enriched with pertinent annotations, including taxonomic classification, combined with metrics needed for quality assessment (coverage depth, average GC content, localization of open reading frames, minority single nucleotide polymorphisms), and incorporates host and disease metadata. Interactive web-based reports with an audit trail are generated. Jovian was employed on four systems, hosted by three institutes, utilizing grid-computers, a high-performance compute singular server, and a Windows10 laptop. All systems yielded identical results with matching MD5sums. Comparison with a commercial online reference tool using viral gastroenteritis samples confirmed the identification of the same pathogens. Jovian provides comparable results to a commercially available online reference tool and generates identical results at different institutes with different IT architectures, proving it is portable and reproducible. Jovian addresses bottlenecks in the deployment of metagenomics within public health and clinical laboratories and has the potential to enhance the breadth of surveillance and testing programs, thereby fostering more effective public health interventions.

Wastewater-based epidemiology (WBE) has emerged as a valuable surveillance tool for SARS-CoV-2 and other pathogens globally, providing insights into community-level infections, including asymptomatic and pre-symptomatic cases. While most WBE programmes focus on quantitative pathogen assessment, next-generation sequencing (NGS) approaches have enabled more detailed analyses, including variant and recombinant genotype identification for viruses like SARS-CoV-2 and poliovirus. Despite recent NGS advancements allowing for the detection of known and novel viruses in wastewater, many of these tools remain underutilised in routine WBE. This short review critically evaluates the applicability of common NGS tools in routine WBE programmes, assessing their capability for identifying emerging threats with epidemic or pandemic potential. Here, we provide evidence-based recommendations for integrating NGS techniques into WBE and the use of results for informed decision-making within a One Health framework, aiming to enhance global infectious disease surveillance and pandemic preparedness. [ABSTRACT FROM AUTHOR]

Achalasia is a rare and complex esophageal disease of unknown etiology characterized by difficulty in swallowing due to the lack of opening of the lower esophageal sphincter and the absence of esophageal peristalsis. Recent advancements in technology for analyzing DNA, RNA and biomolecules in high-throughput techniques are offering new opportunities to better understand the etiology and the pathogenetic mechanisms underlying achalasia. Through this narrative review of the scientific literature, we aim to provide a comprehensive assessment of the state-of-the-art knowledge on omics of achalasia, with particular attention to those considered relevant to the pathogenesis of the disease. The notion and importance of the multi-omics approach, its limitations and future directions are also introduced, and it is highlighted how the integration of single omics data will lead to new insights into the development of achalasia and offer clinical tools which will allow early diagnosis and better patient management. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. IMPORTANCE 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. [ABSTRACT FROM AUTHOR]

Background Echinoderms play crucial roles in coral reef ecosystems, where they are significant detritivores and herbivores. The phylum is widely known for its boom and bust cycles, driven by food availability, predation pressure and mass mortalities. Hence, surveillance of potential pathogens and associates of grossly normal specimens is important to understanding their roles in ecology and mass mortality. Methods We performed viral surveillance in two common coral reef echinoderms, Diadema antillarum and Holothuria floridana, using metagenomics. Urchin specimens were obtained during the 2022 Diadema antillarum scuticociliatosis mass mortality event from the Caribbean and grossly normal H. floridana specimens from a reef in Florida. Viral metagenomes were assembled and aligned against viral genomes and protein encoding regions. Metagenomic reads and previously sequenced transcriptomes were further investigated for putative viral elements by Kraken2. Results D. antillarum was devoid of viruses typically seen in echinoderms, but H. floridana yielded viral taxa similar to those found in other sea cucumbers, including Pisoniviricetes (Picornaviruses), Ellioviricetes (Bunyaviruses), and Magsaviricetes (Nodaviruses). The lack of viruses detected in D. antillarum may be due to the large amount of host DNA in viral metagenomes, or because viruses are less abundant in D. antillarum tissues when compared to H. floridana tissues. Our results also suggest that RNA amplification approach may influence viral representation in viral metagenomes. While our survey was successful in describing viruses associated with both echinoderms, our results indicate that viruses are less pronounced in D. antillarum than in other echinoderms. These results are important in context of wider investigation on the association between viruses and D. antillarum mass mortalities, since the conventional method used in this study was unsuccessful.

Viruses are implicated to play key roles as biogeochemical mediators and ecological drivers in freshwater ecosystems. However, the dynamics of viruses and host associations throughout the seasons and during blooming periods in eutrophic freshwater ecosystems remain poorly understood. From the water microbiomes of planktonic biomass from Lake Taihu, a large eutrophic freshwater lake in China that experiences annual Microcystis-dominated harmful algal blooms (HABs), we recovered 41,997 unique viral clusters spanning a wide taxonomic range, including 15,139 Caudovirales clusters targeting bacteria and 1,044 NCLDV clusters targeting eukaryotes. The viral community exhibited clear seasonal succession, driven primarily by microbial communities (particularly Cyanobacteria and Planctomycetes) and environmental factors (mainly nutrients and temperature). Host prediction revealed that viral infection had a more distinct impact on bacteria-driven nitrogen pathways than on phosphate cycling. HAB-induced variations in microbial composition and environmental conditions affected viral strategies including viral lifestyles, host range, and virus-encoded auxiliary metabolic genes (vAMGs) distributions. Viruses infecting Proteobacteria and Actinobacteria showed an enhanced lysogenic lifestyle and a narrower host range during HAB peak in summer, while viruses infecting Bacteroidota adopted an opposite strategy. Notably, vAMGs were most abundant before the HAB outbreak in spring, compensating for bacterial metabolic processes of their hosts such as carbohydrates metabolism, photosynthesis, and phosphate regulation. The findings highlight the intricate relationships between viruses, host microbes, and the bloom-associated environment, underscoring the important biochemical roles viruses play in eutrophic freshwater ecosystems.

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. Conclusion: 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. [ABSTRACT FROM AUTHOR]

ABSTRACT 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.IMPORTANCEMetagenomics 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.

ABSTRACTInflammatory bowel disease (IBD) is characterized by complex etiology and a disrupted colonic ecosystem. We provide a framework for the analysis of multi-omic data, which we apply to study the gut ecosystem in IBD. Specifically, we train and validate models using data on the metagenome, metatranscriptome, virome, and metabolome from the Human Microbiome Project 2 IBD multi-omic database, with 1,785 repeated samples from 130 individuals (103 cases and 27 controls). After splitting the participants into training and testing groups, we used mixed-effects least absolute shrinkage and selection operator regression to select features for each omic. These features, with demographic covariates, were used to generate separate single-omic prediction scores. All four single-omic scores were then combined into a final regression to assess the relative importance of the individual omics and the predictive benefits when considered together. We identified several species, pathways, and metabolites known to be associated with IBD risk, and we explored the connections between data sets. Individually, metabolomic and viromic scores were more predictive than metagenomics or metatranscriptomics, and when all four scores were combined, we predicted disease diagnosis with a Nagelkerke’s R2 of 0.46 and an area under the curve of 0.80 (95% confidence interval: 0.63, 0.98). Our work supports that some single-omic models for complex traits are more predictive than others, that incorporating multiple omic data sets may improve prediction, and that each omic data type provides a combination of unique and redundant information. This modeling framework can be extended to other complex traits and multi-omic data sets.IMPORTANCEComplex traits are characterized by many biological and environmental factors, such that multi-omic data sets are well-positioned to help us understand their underlying etiologies. We applied a prediction framework across multiple omics (metagenomics, metatranscriptomics, metabolomics, and viromics) from the gut ecosystem to predict inflammatory bowel disease (IBD) diagnosis. The predicted scores from our models highlighted key features and allowed us to compare the relative utility of each omic data set in single-omic versus multi-omic models. Our results emphasized the importance of metabolomics and viromics over metagenomics and metatranscriptomics for predicting IBD status. The greater predictive capability of metabolomics and viromics is likely because these omics serve as markers of lifestyle factors such as diet. This study provides a modeling framework for multi-omic data, and our results show the utility of combining multiple omic data types to disentangle complex disease etiologies and biological signatures.

The 2023 International Virus Bioinformatics Meeting was held in Valencia, Spain, from 24–26 May 2023, attracting approximately 180 participants worldwide. The primary objective of the conference was to establish a dynamic scientific environment conducive to discussion, collaboration, and the generation of novel research ideas. As the first in-person event following the SARS-CoV-2 pandemic, the meeting facilitated highly interactive exchanges among attendees. It served as a pivotal gathering for gaining insights into the current status of virus bioinformatics research and engaging with leading researchers and emerging scientists. The event comprised eight invited talks, 19 contributed talks, and 74 poster presentations across eleven sessions spanning three days. Topics covered included machine learning, bacteriophages, virus discovery, virus classification, virus visualization, viral infection, viromics, molecular epidemiology, phylodynamic analysis, RNA viruses, viral sequence analysis, viral surveillance, and metagenomics. This report provides rewritten abstracts of the presentations, a summary of the key research findings, and highlights shared during the meeting. [ABSTRACT FROM AUTHOR]

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. Conclusion: 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.

Spinach latent virus (SpLV) has been primarily reported in spinach, but recent studies have shown its ability to infect tomato plants as well. In July 2023, a Quebec greenhouse experienced an outbreak of unusual symptoms in tomato plants, including blistering, deformation, mosaic patterns, necrosis, zippering, and chlorotic ringspots. Through genetic analysis, it was confirmed that the plants were infected with SpLV. Phylogenetic analysis revealed genetic relationships between the Canadian isolate and strains from Serbia, the United Kingdom, the United States, and New Zealand. This is the first report of SpLV in tomato plants in Canada, highlighting the need for ongoing surveillance and preventive measures to prevent its further spread. [Extracted from the article]

The black soldier fly (Hermetia illucens, BSF) has emerged as an industrial insect of high promise because of its ability to convert organic waste into nutritious feedstock, making it an environmentally sustainable alternative protein source. As global interest rises, rearing efforts have also been upscaled, which is highly conducive to pathogen transmission. Viral epidemics have stifled mass-rearing efforts of other insects of economic importance, such as crickets, silkworms, and honeybees, but little is known about the viruses that associate with BSF. Although BSFs are thought to be unusually resistant to pathogens because of their expansive antimicrobial gene repertoire, surveillance techniques could be useful in identifying emerging pathogens and common BSF microbes. In this study, we used high-throughput sequencing data to survey BSF larvae and frass samples, and we identified two novel bunyavirus-like sequences. Our phylogenetic analysis grouped one in the family Nairoviridae and the other with two unclassified bunyaviruses. We describe these putative novel viruses as BSF Nairovirus-like 1 and BSF uncharacterized bunyavirus-like 1. We identified candidate segments for the full BSF Nairovirus-like 1 genome using a technique based on transcript co-occurrence and only a partial genome for BSF uncharacterized bunyavirus-like 1. These results emphasize the value of routine BSF colony surveillance and add to the number of viruses associated with BSF. [ABSTRACT FROM AUTHOR]

China is the leading country for pumpkin production in the world. As other cucurbits, diseases caused by viruses are among the serious threats to pumpkin production, but our knowledge on the virus species infecting pumpkin plants is fragmentary. To understand the occurrence of viral diseases on pumpkin, we determined the geographical distribution characteristics, relative abundance and evolutionary relationship of pumpkin infected viruses by meta-transcriptome sequencing (RNA-seq) and viromic analysis of 159 samples exhibited typical viral symptoms collected across China in this study. Totally, 11 known and 3 new viruses were identified. Interestingly, 3 new viruses identified in this study should be positive-sense single-stranded RNA virus whose hosts are prokaryotes. The viruses identified in different sampling locations exhibit significant variations in term of virus species and relative abundance. Here, the results provide valuable information for understanding the virus species and their diversity in cultivated pumpkin across major growing regions of China. • Significant variations through virus species and relative abundance from different regions. • Mixed viral infection are common in almost tested samples. • Expect the known viruses, 3 new viruses infecting prokaryotes were identified in them. [ABSTRACT FROM AUTHOR]

Bacteriophages (phages), which are viruses that infect bacteria, are the most abundant components of microbial communities and play roles in community dynamics and host evolution. However, the study of phage-host interactions is hindered by a paucity of model systems from natural environments. Here, we investigate phage-host interactions in the "pink berry" consortia, which are naturally occurring, low-diversity, macroscopic bacterial aggregates that are found in the Sippewissett Salt Marsh (Falmouth, MA, USA). We leverage metagenomic sequence data and a comparative genomics approach to identify eight compete phage genomes, infer their bacterial hosts from host-encoded clustered regularly interspaced short palindromic repeats (CRISPRs), and observe the potential evolutionary consequences of these interactions. Seven of the eight phages identified infect known pink berry symbionts, namely, Desulfofustis sp. PB-SRB1, Thiohalocapsa sp. PB-PSB1, and Rhodobacteraceae sp. A2, and they are largely divergent from known viruses. In contrast to the conserved bacterial community structure of pink berries, the distribution of these phages across aggregates is highly variable. Two phages persisted over a period of seven years with high sequence conservation, allowing us to identify gene gain and loss. Increased nucleotide variation in a conserved phage capsid gene that is commonly targeted by host CRISPR systems suggests that CRISPRs may drive phage evolution in pink berries. Finally, we identified a predicted phage lysin gene that was horizontally transferred to its bacterial host, potentially via a transposon intermediary. Taken together, our results demonstrate that pink berry consortia contain diverse and variable phages as well as provide evidence for phage-host coevolution via multiple mechanisms in a natural microbial system. [ABSTRACT FROM AUTHOR]

Key points We demonstrate that an unmodified viromic next-generation sequencing methodology effectively detects bacterial pathogen ribosomal RNA in cerebrospinal fluid samples. Sensitivity and specificity displayed pathogen dependent variation. Our finding in principle offers avenues for simultaneous detection of neuropathogenic viruses and bacteria.

Background: In agroecosystems, viruses are well known to influence crop health and some cause phytosanitary and economic problems, but their diversity in non-crop plants and role outside the disease perspective is less known. Extensive virome explorations that include both crop and diverse weed plants are therefore needed to better understand roles of viruses in agroecosystems. Such unbiased exploration is available through viromics, which could generate biological and ecological insights from immense high-throughput sequencing (HTS) data. Results: Here, we implemented HTS-based viromics to explore viral diversity in tomatoes and weeds in farming areas at a nation-wide scale. We detected 125 viruses, including 79 novel species, wherein 65 were found exclusively in weeds. This spanned 21 higher-level plant virus taxa dominated by Potyviridae, Rhabdoviridae, and Tombusviridae, and four non-plant virus families. We detected viruses of non-plant hosts and viroid-like sequences and demonstrated infectivity of a novel tobamovirus in plants of Solanaceae family. Diversities of predominant tomato viruses were variable, in some cases, comparable to that of global isolates of the same species. We phylogenetically classified novel viruses and showed links between a subgroup of phylogenetically related rhabdoviruses to their taxonomically related host plants. Ten classified viruses detected in tomatoes were also detected in weeds, which might indicate possible role of weeds as their reservoirs and that these viruses could be exchanged between the two compartments. Conclusions: We showed that even in relatively well studied agroecosystems, such as tomato farms, a large part of very diverse plant viromes can still be unknown and is mostly present in understudied non-crop plants. The overlapping presence of viruses in tomatoes and weeds implicate possible presence of virus reservoir and possible exchange between the weed and crop compartments, which may influence weed management decisions. The observed variability and widespread presence of predominant tomato viruses and the infectivity of a novel tobamovirus in solanaceous plants, provided foundation for further investigation of virus disease dynamics and their effect on tomato health. The extensive insights we generated from such in-depth agroecosystem virome exploration will be valuable in anticipating possible emergences of plant virus diseases and would serve as baseline for further post-discovery characterization studies. 5s1csuTeBEFLkorHCziRqa Video Abstract [ABSTRACT FROM AUTHOR]

Cyanophages exert important top-down controls on their cyanobacteria hosts; however, concurrent analysis of both phage and host populations is needed to better assess phage–host interaction models. We analyzed picocyanobacteria Prochlorococcus and Synechococcus and T4-like cyanophage communities in Pacific Ocean surface waters using five years of monthly viral and cellular fraction metagenomes. Cyanophage communities contained thousands of mostly low-abundance (<2% relative abundance) species with varying temporal dynamics, categorized as seasonally recurring or non-seasonal and occurring persistently, occasionally, or sporadically (detected in ≥85%, 15-85%, or <15% of samples, respectively). Viromes contained mostly seasonal and persistent phages (~40% each), while cellular fraction metagenomes had mostly sporadic species (~50%), reflecting that these sample sets capture different steps of the infection cycle—virions from prior infections or within currently infected cells, respectively. Two groups of seasonal phages correlated to Synechococcus or Prochlorococcus were abundant in spring/summer or fall/winter, respectively. Cyanophages likely have a strong influence on the host community structure, as their communities explained up to 32% of host community variation. These results support how both seasonally recurrent and apparent stochastic processes, likely determined by host availability and different host-range strategies among phages, are critical to phage–host interactions and dynamics, consistent with both the Kill-the-Winner and the Bank models. [ABSTRACT FROM AUTHOR]

Simple Summary: Proteomics is a booming field in life sciences and, increasingly, is not only based on mass spectrometry (MS), but also on multiplex bead or aptamer assays and proximity extension assays. The use of untargeted MS generates big data sets in little time, but it also has limitations. Here, we discuss the plausibility of screening proteomic shotgun MS raw data for viral proteins in human gastric biopsies. Though this is technically possible and, thus, appealing to researchers, low-abundant proteins of guest species are barely present at suitable concentrations for measurement. Still, the processing algorithms will return hits due to chance assignments of low-quality spectra, but these should be red-flagged. A sanity check needs to establish whether or not certain proteins can be available at a sufficient concentration for measurement in the sample at all. Not every possible analysis is, thus, sensible. Even though both instrumentation and bioinformatic processing are continuously improving, a quality control of the data output will always be advisable. This paper uses practical examples to explain difficulties in spectral assignment leading to false-positive protein matches and is, thus, a tutorial for laymen and novices in MS-based proteomics. (1) Background: Untargeted mass spectrometry (MS)-based proteomic analysis is highly amenable to automation. Software algorithms translate raw spectral data into protein information obtained by a comparison to sequence databases. However, the technology has limitations, especially for analytes measured at the limit of detection. In a protein expression study of human gastric biopsies, the question arose whether or not it is possible, as well as sensible, to search for viral proteins in addition to those from the human host. (2) Methods: Experimental data-independent MS data were analyzed using protein sequences for oncoviruses, and BLAST analyses were performed to elucidate the level of sequence homology to host proteins. (3) Results: About one hundred viral proteins were assigned, but there was also up to 43% sequence homology to human proteins. (4) Conclusions: There are at least two reasons why the matches to viral proteins should be used with care. First, it is not plausible that large amounts of viral proteins should be present in human gastric biopsies, so the spectral quality of the peptides derived from viral proteins is likely low. As a consequence, the number of false assignments is high. Second, homologous peptides found both in human and virus proteomes contribute to matching errors. Thus, though shotgun proteomics raw data can technically be analyzed using any database, meaningful results cannot be always expected and a sanity check must be performed. Both instrumentation and bioinformatic processing in MS-based proteomics are continuously improving at lowering the limit of detection even further. Nevertheless, data output should always be controlled in order to avoid the over-interpretation of results. [ABSTRACT FROM AUTHOR]

In this study, a total of 41,997 viral clusters were identified in surface water metagenomes from China's eutrophic Lake Taihu. We delineated significant fluctuations in various viral characteristics throughout the year with the outbreak and decline of HABs. These fluctuations encompassed alterations in viral community structure, virus-host interactions, viral lifecycles, host ranges, and vAMGs. The observed dynamics underscored viruses as one of the crucial ecological drivers in eutrophic water environments, and untangled the ecological links between viruses, host microbes and water environment in the eutrophic freshwater ecosystem with cyanobacterial HABs. [Display omitted] • The viral community in Lake Taihu underwent distinct seasonal succession. • Environmental factors and microbial hosts co-drove the viral community structure. • Water viruses could affect the bacteria-driven nitrogen and phosphate cycling through infection. • Viral strategies could be affected by bloom-induced environmental variations. • Viruses in Lake Taihu encoded auxiliary metabolic genes involved in central carbon metabolism. Viruses are implicated to play key roles as biogeochemical mediators and ecological drivers in freshwater ecosystems. However, the dynamics of viruses and host associations throughout the seasons and during blooming periods in eutrophic freshwater ecosystems remain poorly understood. From the water microbiomes of planktonic biomass from Lake Taihu, a large eutrophic freshwater lake in China that experiences annual Microcystis -dominated harmful algal blooms (HABs), we recovered 41,997 unique viral clusters spanning a wide taxonomic range, including 15,139 Caudovirales clusters targeting bacteria and 1,044 NCLDV clusters targeting eukaryotes. The viral community exhibited clear seasonal succession, driven primarily by microbial communities (particularly Cyanobacteria and Planctomycetes) and environmental factors (mainly nutrients and temperature). Host prediction revealed that viral infection had a more distinct impact on bacteria-driven nitrogen pathways than on phosphate cycling. HAB-induced variations in microbial composition and environmental conditions affected viral strategies including viral lifestyles, host range, and virus-encoded auxiliary metabolic genes (vAMGs) distributions. Viruses infecting Proteobacteria and Actinobacteria showed an enhanced lysogenic lifestyle and a narrower host range during HAB peak in summer, while viruses infecting Bacteroidota adopted an opposite strategy. Notably, vAMGs were most abundant before the HAB outbreak in spring, compensating for bacterial metabolic processes of their hosts such as carbohydrates metabolism, photosynthesis, and phosphate regulation. The findings highlight the intricate relationships between viruses, host microbes, and the bloom-associated environment, underscoring the important biochemical roles viruses play in eutrophic freshwater ecosystems. [ABSTRACT FROM AUTHOR]

Background: In patients with central nervous system (CNS) infections identification of the causative pathogen is important for treatment. Metagenomic next-generation sequencing techniques are increasingly being applied to identify causes of CNS infections, as they can detect any pathogen nucleic acid sequences present. Viromic techniques that enrich samples for virus particles prior to sequencing may simultaneously enrich ribosomes from bacterial pathogens, which are similar in size to small viruses. Methods: We studied the performance of a viromic library preparation technique (VIDISCA) combined with low-depth IonTorrent sequencing (median ~ 25,000 reads per sample) for detection of ribosomal RNA from common pathogens, analyzing 89 cerebrospinal fluid samples from patients with culture proven bacterial meningitis. Results: Sensitivity and specificity to Streptococcus pneumoniae (n = 24) before and after optimizing threshold parameters were 79% and 52%, then 88% and 90%. Corresponding values for Neisseria meningitidis (n = 22) were 73% and 93%, then 67% and 100%, Listeria monocytogenes (n = 24) 21% and 100%, then 27% and 100%, and Haemophilus influenzae (n = 18) 56% and 100%, then 71% and 100%. A higher total sequencing depth, no antibiotic treatment prior to lumbar puncture, increased disease severity, and higher c-reactive protein levels were associated with pathogen detection. Conclusion: We provide proof of principle that a viromic approach can be used to correctly identify bacterial ribosomal RNA in patients with bacterial meningitis. Further work should focus on increasing assay sensitivity, especially for problematic species (e.g. L. monocytogenes), as well as profiling additional pathogens. The technique is most suited to research settings and examination of idiopathic cases, rather than an acute clinical setting. Key points: We demonstrate that an unmodified viromic next-generation sequencing methodology effectively detects bacterial pathogen ribosomal RNA in cerebrospinal fluid samples. Sensitivity and specificity displayed pathogen dependent variation. Our finding in principle offers avenues for simultaneous detection of neuropathogenic viruses and bacteria. [ABSTRACT FROM AUTHOR]

Viruses are key members of Earth's microbiomes, shaping microbial community composition and metabolism. Here, we describe recent advances in 'soil viromics', that is, virus-focused metagenome and metatranscriptome analyses that offer unprecedented windows into the soil virosphere. Given the emerging picture of high soil viral activity, diversity, and dynamics over short spatiotemporal scales, we then outline key eco-evolutionary processes that we hypothesize are the major diversity drivers for soil viruses. We argue that a community effort is needed to establish a 'global soil virosphere atlas' that can be used to address the roles of viruses in soil microbiomes and terrestrial biogeochemical cycles across spatiotemporal scales. Targeted soil viral metagenomes (viromes) enable in-depth exploration of encapsidated genetic material in soil. Extra-large-scale combined assemblies can reveal rare viruses otherwise missed from total metagenomes. RNA-based metatranscriptomes and viromes provide insights into substantial RNA virus diversity in soil. Viromics combined with laboratory approaches for evaluating viral activity and virus–host interactions, including controlled incubations, cultivation, single-cell approaches, and microscopy, will form the framework for addressing long-standing soil viral ecology questions. We posit that soils represent the 'perfect storm' of diversity drivers, including spatiotemporal dynamics, physicochemical heterogeneity, and occasional immigrations, resulting in highly diverse and dynamic viral communities. [ABSTRACT FROM AUTHOR]

Background: The rhizosphere is a hotspot for microbial activity and contributes to ecosystem services including plant health and biogeochemical cycling. The activity of microbial viruses, and their influence on plant-microbe interactions in the rhizosphere, remains undetermined. Given the impact of viruses on the ecology and evolution of their host communities, determining how soil viruses influence microbiome dynamics is crucial to build a holistic understanding of rhizosphere functions. Results: Here, we aimed to investigate the influence of crop management on the composition and activity of bulk soil, rhizosphere soil, and root viral communities. We combined viromics, metagenomics, and metatranscriptomics on soil samples collected from a 3-year crop rotation field trial of oilseed rape (Brassica napus L.). By recovering 1059 dsDNA viral populations and 16,541 ssRNA bacteriophage populations, we expanded the number of underexplored Leviviricetes genomes by > 5 times. Through detection of viral activity in metatranscriptomes, we uncovered evidence of "Kill-the-Winner" dynamics, implicating soil bacteriophages in driving bacterial community succession. Moreover, we found the activity of viruses increased with proximity to crop roots, and identified that soil viruses may influence plant-microbe interactions through the reprogramming of bacterial host metabolism. We have provided the first evidence of crop rotation-driven impacts on soil microbial communities extending to viruses. To this aim, we present the novel principal of "viral priming," which describes how the consecutive growth of the same crop species primes viral activity in the rhizosphere through local adaptation. Conclusions: Overall, we reveal unprecedented spatial and temporal diversity in viral community composition and activity across root, rhizosphere soil, and bulk soil compartments. Our work demonstrates that the roles of soil viruses need greater consideration to exploit the rhizosphere microbiome for food security, food safety, and environmental sustainability. 82WLDaaCyWkoR4_rMFNxLJ Video Abstract [ABSTRACT FROM AUTHOR]

Wastewater-based epidemiology (WBE) has emerged as a valuable surveillance tool for SARS-CoV-2 and other pathogens globally, providing insights into community-level infections, including asymptomatic and pre-symptomatic cases. While most WBE programmes focus on quantitative pathogen assessment, next-generation sequencing (NGS) approaches have enabled more detailed analyses, including variant and recombinant genotype identification for viruses like SARS-CoV-2 and poliovirus. Despite recent NGS advancements allowing for the detection of known and novel viruses in wastewater, many of these tools remain underutilised in routine WBE. This short review critically evaluates the applicability of common NGS tools in routine WBE programmes, assessing their capability for identifying emerging threats with epidemic or pandemic potential. Here, we provide evidence-based recommendations for integrating NGS techniques into WBE and the use of results for informed decision-making within a One Health framework, aiming to enhance global infectious disease surveillance and pandemic preparedness., Competing Interests: Declarations. Conflicts of interest: The authors declare no competing interests., (© 2024. The Author(s).)

Background: Echinoderms play crucial roles in coral reef ecosystems, where they are significant detritivores and herbivores. The phylum is widely known for its boom and bust cycles, driven by food availability, predation pressure and mass mortalities. Hence, surveillance of potential pathogens and associates of grossly normal specimens is important to understanding their roles in ecology and mass mortality., Methods: We performed viral surveillance in two common coral reef echinoderms, Diadema antillarum and Holothuria floridana , using metagenomics. Urchin specimens were obtained during the 2022 Diadema antillarum scuticociliatosis mass mortality event from the Caribbean and grossly normal H. floridana specimens from a reef in Florida. Viral metagenomes were assembled and aligned against viral genomes and protein encoding regions. Metagenomic reads and previously sequenced transcriptomes were further investigated for putative viral elements by Kraken2., Results: D. antillarum was devoid of viruses typically seen in echinoderms, but H. floridana yielded viral taxa similar to those found in other sea cucumbers, including Pisoniviricetes (Picornaviruses), Ellioviricetes (Bunyaviruses), and Magsaviricetes (Nodaviruses). The lack of viruses detected in D. antillarum may be due to the large amount of host DNA in viral metagenomes, or because viruses are less abundant in D. antillarum tissues when compared to H. floridana tissues. Our results also suggest that RNA amplification approach may influence viral representation in viral metagenomes. While our survey was successful in describing viruses associated with both echinoderms, our results indicate that viruses are less pronounced in D. antillarum than in other echinoderms. These results are important in context of wider investigation on the association between viruses and D. antillarum mass mortalities, since the conventional method used in this study was unsuccessful., Competing Interests: Mya Breitbart is an Academic Editor for PeerJ., (©2024 Hewson et al.)

Abstract Background Peatlands are expected to experience sustained yet fluctuating higher temperatures due to climate change, leading to increased microbial activity and greenhouse gas emissions. Despite mounting evidence for viral contributions to these processes in peatlands underlain with permafrost, little is known about viruses in other peatlands. More generally, soil viral biogeography and its potential drivers are poorly understood at both local and global scales. Here, 87 metagenomes and five viral size-fraction metagenomes (viromes) from a boreal peatland in northern Minnesota (the SPRUCE whole-ecosystem warming experiment and surrounding bog) were analyzed for dsDNA viral community ecological patterns, and the recovered viral populations (vOTUs) were compared with our curated PIGEON database of 266,125 vOTUs from diverse ecosystems. Results Within the SPRUCE experiment, viral community composition was significantly correlated with peat depth, water content, and carbon chemistry, including CH4 and CO2 concentrations, but not with temperature during the first 2 years of warming treatments. Peat vOTUs with aquatic-like signatures (shared predicted protein content with marine and/or freshwater vOTUs) were significantly enriched in more waterlogged surface peat depths. Predicted host ranges for SPRUCE vOTUs were relatively narrow, generally within a single bacterial genus. Of the 4326 SPRUCE vOTUs, 164 were previously detected in other soils, mostly peatlands. None of the previously identified 202,371 marine and freshwater vOTUs in our PIGEON database were detected in SPRUCE peat, but 0.4% of 80,714 viral clusters (VCs, grouped by predicted protein content) were shared between soil and aquatic environments. On a per-sample basis, vOTU recovery was 32 times higher from viromes compared with total metagenomes. Conclusions Results suggest strong viral “species” boundaries between terrestrial and aquatic ecosystems and to some extent between peat and other soils, with differences less pronounced at higher taxonomic levels. The significant enrichment of aquatic-like vOTUs in more waterlogged peat suggests that viruses may also exhibit niche partitioning on more local scales. These patterns are presumably driven in part by host ecology, consistent with the predicted narrow host ranges. Although more samples and increased sequencing depth improved vOTU recovery from total metagenomes, the substantially higher per-sample vOTU recovery after viral particle enrichment highlights the utility of soil viromics. Video abstract The importance of Minnesota peat viromes in revealing terrestrial and aquatic niche partitioning for viral populations

The black soldier fly (Hermetia illucens, BSF) has emerged as an industrial insect of high promise because of its ability to convert organic waste into nutritious feedstock, making it an environmentally sustainable alternative protein source. As global interest rises, rearing efforts have also been upscaled, which is highly conducive to pathogen transmission. Viral epidemics have stifled mass-rearing efforts of other insects of economic importance, such as crickets, silkworms, and honeybees, but little is known about the viruses that associate with BSF. Although BSFs are thought to be unusually resistant to pathogens because of their expansive antimicrobial gene repertoire, surveillance techniques could be useful in identifying emerging pathogens and common BSF microbes. In this study, we used high-throughput sequencing data to survey BSF larvae and frass samples, and we identified two novel bunyavirus-like sequences. Our phylogenetic analysis grouped one in the family Nairoviridae and the other with two unclassified bunyaviruses. We describe these putative novel viruses as BSF Nairovirus-like 1 and BSF uncharacterized bunyavirus-like 1. We identified candidate segments for the full BSF Nairovirus-like 1 genome using a technique based on transcript co-occurrence and only a partial genome for BSF uncharacterized bunyavirus-like 1. These results emphasize the value of routine BSF colony surveillance and add to the number of viruses associated with BSF.

Viruses are expected to be pivotal members of soil ecosystems, and recent advances in viral size fraction metagenomic (viromic) approaches have improved our ability to interrogate soil viral ecology. However, viromics relies on extraction buffers to effectively desorb viral particles from the soil matrix for downstream analysis, and viral extraction efficiency could be affected by the interplay between viral particles, soils, and extraction buffer chemistry. Here, we investigated whether extraction buffer chemistry affected extractable viral community composition measured by viromics from different soil types, for both biological (samples collected 1 m apart) and technical (subsamples from the same soil homogenate) replicates. We investigated pH manipulation of protein-supplemented phosphate-buffered saline buffer (PPBS, pHs 4.5, 5.5, 6.5, and 7.5) on forest, grassland and wetland soils that exhibited different soil edaphic properties, and we tested different buffer chemistries (PPBS, Carbonated Buffer, Glycine, and Saline Magnesium) on just the wetland soil. Spatial distance (i.e., biological replicate) was the primary driver of extractable viral community composition across all buffers and soils tested. Differences in viral community composition according to extraction buffer properties were only observed in the grassland technical replicates at PPBS buffer pH 4.5, and in both the wetland technical and biological replicates treated with different buffer chemistries, but the effects of buffer chemistry were secondary to spatial distance in the biological replicates. The lack of buffering capacity in the grassland soil technical replicates likely increased sorption of viral particles at pH 4.5, but neither protein composition nor isoelectric point explained this phenomenon. Given that most soil viral ecological studies to date include sample collection over distances much farther apart than the 1-m distances considered here, results suggest that extraction buffer chemistry is likely of much lower importance than ecological considerations, such as spatial distance, in the design of future soil viral ecological investigations. • Spatial distance was the main driver of extractable viral community composition. • Extraction buffer chemistry secondarily structured wetland viral communities. • At pH 4.5, PPBS buffer likely increased viral sorption in homogenized grassland soil. • Increased sorption was not explained by estimated viral protein isoelectric points. [ABSTRACT FROM AUTHOR]

Abstract Background Viruses are the most abundant biological entities on Earth, known to be crucial components of microbial ecosystems. However, there is little information on the viral community within agricultural waste. There are currently ~ 2.7 million dairy cattle in the UK producing 7–8% of their own bodyweight in manure daily, and 28 million tonnes annually. To avoid pollution of UK freshwaters, manure must be stored and spread in accordance with guidelines set by DEFRA. Manures are used as fertiliser, and widely spread over crop fields, yet little is known about their microbial composition. We analysed the virome of agricultural slurry over a 5-month period using short and long-read sequencing. Results Hybrid sequencing uncovered more high-quality viral genomes than long or short-reads alone; yielding 7682 vOTUs, 174 of which were complete viral genomes. The slurry virome was highly diverse and dominated by lytic bacteriophage, the majority of which represent novel genera (~ 98%). Despite constant influx and efflux of slurry, the composition and diversity of the slurry virome was extremely stable over time, with 55% of vOTUs detected in all samples over a 5-month period. Functional annotation revealed a diverse and abundant range of auxiliary metabolic genes and novel features present in the community, including the agriculturally relevant virulence factor VapE, which was widely distributed across different phage genera that were predicted to infect several hosts. Furthermore, we identified an abundance of phage-encoded diversity-generating retroelements, which were previously thought to be rare on lytic viral genomes. Additionally, we identified a group of crAssphages, including lineages that were previously thought only to be found in the human gut. Conclusions The cattle slurry virome is complex, diverse and dominated by novel genera, many of which are not recovered using long or short-reads alone. Phages were found to encode a wide range of AMGs that are not constrained to particular groups or predicted hosts, including virulence determinants and putative ARGs. The application of agricultural slurry to land may therefore be a driver of bacterial virulence and antimicrobial resistance in the environment. Video abstract

Abstract Background Viruses directly affect the most important biological processes in the ocean via their regulation of prokaryotic and eukaryotic populations. Marine sponges form stable symbiotic partnerships with a wide diversity of microorganisms and this high symbiont complexity makes them an ideal model for studying viral ecology. Here, we used morphological and molecular approaches to illuminate the diversity and function of viruses inhabiting nine sponge species from the Great Barrier Reef and seven from the Red Sea. Results Viromic sequencing revealed host-specific and site-specific patterns in the viral assemblages, with all sponge species dominated by the bacteriophage order Caudovirales but also containing variable representation from the nucleocytoplasmic large DNA virus families Mimiviridae, Marseilleviridae, Phycodnaviridae, Ascoviridae, Iridoviridae, Asfarviridae and Poxviridae. Whilst core viral functions related to replication, infection and structure were largely consistent across the sponge viromes, functional profiles varied significantly between species and sites largely due to differential representation of putative auxiliary metabolic genes (AMGs) and accessory genes, including those associated with herbicide resistance, heavy metal resistance and nylon degradation. Furthermore, putative AMGs varied with the composition and abundance of the sponge-associated microbiome. For instance, genes associated with antimicrobial activity were enriched in low microbial abundance sponges, genes associated with nitrogen metabolism were enriched in high microbial abundance sponges and genes related to cellulose biosynthesis were enriched in species that host photosynthetic symbionts. Conclusions Our results highlight the diverse functional roles that viruses can play in marine sponges and are consistent with our current understanding of sponge ecology. Differential representation of putative viral AMGs and accessory genes across sponge species illustrate the diverse suite of beneficial roles viruses can play in the functional ecology of these complex reef holobionts. Video Abstract

(1) Background: Untargeted mass spectrometry (MS)-based proteomic analysis is highly amenable to automation. Software algorithms translate raw spectral data into protein information obtained by a comparison to sequence databases. However, the technology has limitations, especially for analytes measured at the limit of detection. In a protein expression study of human gastric biopsies, the question arose whether or not it is possible, as well as sensible, to search for viral proteins in addition to those from the human host. (2) Methods: Experimental data-independent MS data were analyzed using protein sequences for oncoviruses, and BLAST analyses were performed to elucidate the level of sequence homology to host proteins. (3) Results: About one hundred viral proteins were assigned, but there was also up to 43% sequence homology to human proteins. (4) Conclusions: There are at least two reasons why the matches to viral proteins should be used with care. First, it is not plausible that large amounts of viral proteins should be present in human gastric biopsies, so the spectral quality of the peptides derived from viral proteins is likely low. As a consequence, the number of false assignments is high. Second, homologous peptides found both in human and virus proteomes contribute to matching errors. Thus, though shotgun proteomics raw data can technically be analyzed using any database, meaningful results cannot be always expected and a sanity check must be performed. Both instrumentation and bioinformatic processing in MS-based proteomics are continuously improving at lowering the limit of detection even further. Nevertheless, data output should always be controlled in order to avoid the over-interpretation of results.

Cyanophages exert important top-down controls on their cyanobacteria hosts; however, concurrent analysis of both phage and host populations is needed to better assess phage–host interaction models. We analyzed picocyanobacteria Prochlorococcus and Synechococcus and T4-like cyanophage communities in Pacific Ocean surface waters using five years of monthly viral and cellular fraction metagenomes. Cyanophage communities contained thousands of mostly low-abundance (Synechococcus or Prochlorococcus were abundant in spring/summer or fall/winter, respectively. Cyanophages likely have a strong influence on the host community structure, as their communities explained up to 32% of host community variation. These results support how both seasonally recurrent and apparent stochastic processes, likely determined by host availability and different host-range strategies among phages, are critical to phage–host interactions and dynamics, consistent with both the Kill-the-Winner and the Bank models.

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., Competing Interests: Competing interests The authors declare no competing interests.

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., Importance: 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., Competing Interests: The authors declare no conflict of interest.

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., Importance: 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., Competing Interests: The authors declare no conflict of interest.

Background: Peatlands are expected to experience sustained yet fluctuating higher temperatures due to climate change, leading to increased microbial activity and greenhouse gas emissions. Despite mounting evidence for viral contributions to these processes in peatlands underlain with permafrost, little is known about viruses in other peatlands. More generally, soil viral biogeography and its potential drivers are poorly understood at both local and global scales. Here, 87 metagenomes and five viral size-fraction metagenomes (viromes) from a boreal peatland in northern Minnesota (the SPRUCE whole-ecosystem warming experiment and surrounding bog) were analyzed for dsDNA viral community ecological patterns, and the recovered viral populations (vOTUs) were compared with our curated PIGEON database of 266,125 vOTUs from diverse ecosystems. Results: Within the SPRUCE experiment, viral community composition was significantly correlated with peat depth, water content, and carbon chemistry, including CH4 and CO2 concentrations, but not with temperature during the first 2 years of warming treatments. Peat vOTUs with aquatic-like signatures (shared predicted protein content with marine and/or freshwater vOTUs) were significantly enriched in more waterlogged surface peat depths. Predicted host ranges for SPRUCE vOTUs were relatively narrow, generally within a single bacterial genus. Of the 4326 SPRUCE vOTUs, 164 were previously detected in other soils, mostly peatlands. None of the previously identified 202,371 marine and freshwater vOTUs in our PIGEON database were detected in SPRUCE peat, but 0.4% of 80,714 viral clusters (VCs, grouped by predicted protein content) were shared between soil and aquatic environments. On a per-sample basis, vOTU recovery was 32 times higher from viromes compared with total metagenomes. Conclusions: Results suggest strong viral "species" boundaries between terrestrial and aquatic ecosystems and to some extent between peat and other soils, with differences less pronounced at higher taxonomic levels. The significant enrichment of aquatic-like vOTUs in more waterlogged peat suggests that viruses may also exhibit niche partitioning on more local scales. These patterns are presumably driven in part by host ecology, consistent with the predicted narrow host ranges. Although more samples and increased sequencing depth improved vOTU recovery from total metagenomes, the substantially higher per-sample vOTU recovery after viral particle enrichment highlights the utility of soil viromics. 3EUUqCyiCvMAAvxFuvvQVm Video abstract The importance of Minnesota peat viromes in revealing terrestrial and aquatic niche partitioning for viral populations [ABSTRACT FROM AUTHOR]

ABSTRACT The small genomes of most viruses make it difficult to fully capture viral diversity in metagenomes dominated by DNA from cellular organisms. Viral size fraction metagenomics (viromics) protocols facilitate the enrichment of viral DNA from environmental samples, and these protocols typically include DNase treatment of the post-0.2-μm-filtered viromic fraction to remove contaminating free DNA prior to virion lysis. However, DNase may also remove desirable viral genomic DNA (e.g., contained in virions compromised due to frozen storage or laboratory processing), suggesting that DNase-untreated viromes might be useful in some cases. In order to understand how virome preparation with and without DNase treatment influences the resultant data, here, we compared 15 soil viromes (7 DNase treated and 8 untreated) from 8 samples collected from agricultural fields prior to tomato planting. DNase-treated viromes yielded significantly more assembled viral contigs, contained significantly less nonviral microbial DNA, and recovered more viral populations (viral operational taxonomic units [vOTUs]) through read mapping. However, DNase-treated and untreated viromes were statistically indistinguishable in terms of ecological patterns across viral communities. Although the results suggest that DNase treatment is preferable where possible, in comparison to previously reported total metagenomes from the same samples, both DNase-treated and untreated viromes were significantly enriched in viral signatures by all metrics compared, including a 225-times-higher proportion of viral reads in untreated viromes compared to total metagenomes. Thus, even without DNase treatment, viromics was preferable to total metagenomics for capturing viral diversity in these soils, suggesting that preparation of DNase-untreated viromes can be worthwhile when DNase treatment is not possible. IMPORTANCE Viromics is becoming an increasingly popular method for characterizing soil viral communities. DNase treatment of the viral size fraction prior to DNA extraction is meant to reduce contaminating free DNA and is a common step within viromics protocols to ensure that sequences are of viral origin. However, some samples may not be amenable to DNase treatment due to viral particles being compromised either in storage (i.e., frozen) or during other sample processing steps. To date, the effect of DNase treatment on the recovery of viruses and downstream ecological interpretations of soil viral communities is not thoroughly understood. This work sheds light on these questions and indicates that while DNase treatment of soil viromes improves the recovery of viral populations, this improvement is modest in comparison to the gains made by viromics over total soil metagenomics. Furthermore, DNase treatment may not be necessary to observe the ecological patterns structuring soil viral communities.

• The novel viral community involved in CWW treatment system was studied by viromics. • The diversities of viruses and AMGs decreased along the CWW treatment process. • Viral AMGs are involved in contaminants removal and resistance to environmental stresses. • The hosts of viruses were dominantly Pseudomonas, Acidovorax and Thauera genera. • The symbiotic virus-bacteria interaction patterns in CWW treatment were proposed. 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. [Display omitted] [ABSTRACT FROM AUTHOR]

Background Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). Results The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (≥3 kbp) contigs, while k-mer- and blast-based tools were uniquely able to detect viruses from short (≤3 kbp) contigs. Notably, however, the performance increase of k-mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to ∼5% for virome and ∼75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. For viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from ∼95% (whole genomes) down to ∼80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. Conclusion Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses ‘hidden’ in diverse sequence datasets.

Background. Viruses influence global patterns of microbial diversity and nutrient cycles. Though viral metagenomics (viromics), specifically targeting dsDNA viruses, has been critical for revealing viral roles across diverse ecosystems, its analyses differ in many ways from those used for microbes. To date, viromics benchmarking has covered read pre-processing, assembly, relative abundance, read mapping thresholds and diversity estimation, but other steps would benefit from benchmarking and standardization. Here we use in silico-generated datasets and an extensive literature survey to evaluate and highlight how dataset composition (i.e., viromes vs bulk metagenomes) and assembly fragmentation impact (i) viral contig identification tool, (ii) virus taxonomic classification, and (iii) identification and curation of auxiliary metabolic genes (AMGs). Results. The in silico benchmarking of five commonly used virus identification tools show that gene-content-based tools consistently performed well for long (-3 kbp) contigs, while k-mer- and blast-based tools were uniquely able to detect viruses from short (-3 kbp) contigs. Notably, however, the performance increase of k-mer- and blast-based tools for short contigs was obtained at the cost of increased false positives (sometimes up to -5% for virome and -75% bulk samples), particularly when eukaryotic or mobile genetic element sequences were included in the test datasets. For viral classification, variously sized genome fragments were assessed using gene-sharing network analytics to quantify drop-offs in taxonomic assignments, which revealed correct assignations ranging from -95% (whole genomes) down to -80% (3 kbp sized genome fragments). A similar trend was also observed for other viral classification tools such as VPF-class, ViPTree and VIRIDIC, suggesting that caution is warranted when classifying short genome fragments and not full genomes. Finally, we highlight how fragmented assemblies can lead to erroneous identification of AMGs and outline a best-practices workflow to curate candidate AMGs in viral genomes assembled from metagenomes. Conclusion. Together, these benchmarking experiments and annotation guidelines should aid researchers seeking to best detect, classify, and characterize the myriad viruses 'hidden' in diverse sequence datasets. [ABSTRACT FROM AUTHOR]

Background: Viruses are the most abundant biological entities on Earth, known to be crucial components of microbial ecosystems. However, there is little information on the viral community within agricultural waste. There are currently ~ 2.7 million dairy cattle in the UK producing 7–8% of their own bodyweight in manure daily, and 28 million tonnes annually. To avoid pollution of UK freshwaters, manure must be stored and spread in accordance with guidelines set by DEFRA. Manures are used as fertiliser, and widely spread over crop fields, yet little is known about their microbial composition. We analysed the virome of agricultural slurry over a 5-month period using short and long-read sequencing. Results: Hybrid sequencing uncovered more high-quality viral genomes than long or short-reads alone; yielding 7682 vOTUs, 174 of which were complete viral genomes. The slurry virome was highly diverse and dominated by lytic bacteriophage, the majority of which represent novel genera (~ 98%). Despite constant influx and efflux of slurry, the composition and diversity of the slurry virome was extremely stable over time, with 55% of vOTUs detected in all samples over a 5-month period. Functional annotation revealed a diverse and abundant range of auxiliary metabolic genes and novel features present in the community, including the agriculturally relevant virulence factor VapE, which was widely distributed across different phage genera that were predicted to infect several hosts. Furthermore, we identified an abundance of phage-encoded diversity-generating retroelements, which were previously thought to be rare on lytic viral genomes. Additionally, we identified a group of crAssphages, including lineages that were previously thought only to be found in the human gut. Conclusions: The cattle slurry virome is complex, diverse and dominated by novel genera, many of which are not recovered using long or short-reads alone. Phages were found to encode a wide range of AMGs that are not constrained to particular groups or predicted hosts, including virulence determinants and putative ARGs. The application of agricultural slurry to land may therefore be a driver of bacterial virulence and antimicrobial resistance in the environment. C9xR_Dnuto-w_HvVTTDj7q Video abstract [ABSTRACT FROM AUTHOR]

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., Competing Interests: The authors declare no conflicts of interest., (© The Author(s) 2024. Published by Oxford University Press on behalf of the International Society for Microbial Ecology.)

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., Competing Interests: None declared., (© The Author(s) 2024. Published by Oxford University Press.)