Metatranscriptomics reveals system-specific viral adaptive strategies and prokaryotic defense trade-offs across anaerobic digestion systems.

Marine animal epidermal surfaces act as a transitional viral habitat-an epidermal ecotone-between tissues and the environment, supporting diverse tripartite relationships between animals, microbes, and viruses, which have yet to be investigated. In this review, we synthesize the viral ecology of marine animal epidermal tissues, surfaces, and aura biomes to identify knowledge gaps and highlight the value of marine animal epidermis as a novel model system for microbiome research.

Taiwan, a region traditionally considered non-endemic for dengue, experienced an unexpected and large-scale outbreak in 2023. We investigated the multifactorial drivers of this outbreak, including cross-border viral importation, serotype cocirculation, vector ecology, and climate variability. We analyzed national dengue surveillance data (2013-2023), meteorological records, and Breteau Index (BI) values, alongside molecular serotyping and whole-genome sequencing of clinical isolates. Time-lagged Poisson regression was used to identify predictors of indigenous dengue transmission in Kaohsiung and Tainan. Full-genome comparisons were conducted between 2023 strains and historical epidemic isolates. A total of 26 706 laboratory-confirmed cases were reported, primarily in Tainan (80.7%) and Kaohsiung (11.9%). Real-time RT-PCR identified cocirculating DENV-1 and DENV-2 strains. Phylogenetic analysis confirmed the 2023 DENV-1 and DENV-2 strains were genetically linked to contemporary strains from Southeast Asian countries. Whole-genome sequencing identified several nonsynonymous mutations in the NS2A, NS3, and NS5 regions when compared with historical outbreak isolates. Time-lagged regression showed that imported cases, precipitation, and the BI were associated with incidence in univariate models. In Kaohsiung, the best-fitting multivariable model included the BI, but temperature and precipitation were the independent predictors. In Tainan, precipitation and, at longer lags, imported cases were more influential, while the BI lost significance after adjustment. The 2023 dengue outbreak in Taiwan was driven by a complex interplay between viral introductions, climatic conditions, and vector dynamics. The differing transmission drivers observed between cities highlight the need for region-specific vector surveillance, climate-informed early warning systems, and sustained genomic monitoring to prevent future re-emergence of dengue in this non-endemic setting.

Hot springs represent unique geothermal ecosystems where extreme physicochemical conditions intersect with remarkable microbial diversity and metabolic innovation. These natural laboratories harbor specialized communities of thermophilic and hyperthermophilic microorganisms that have evolved exceptional adaptations to elevated temperatures, extreme pH, and high salinity. This review synthesizes current understanding of hot spring systems as multifunctional natural resources, examining their roles in fundamental microbiology, biotechnology, and sustainable development. We explore the ecological principles governing microbial community assembly, the taxonomic and functional diversity of prokaryotic and eukaryotic microorganisms, and the genomic mechanisms underlying thermophilic adaptation. Hot springs yield enzymes revolutionizing molecular biology and industrial catalysis, bioactive metabolites with pharmaceutical potential, and novel bioremediation capabilities including plastic degradation. Beyond biological significance, these systems contain valuable minerals and rare earth elements, supporting an emerging bioeconomy integrating wellness tourism, bioprospecting, and sustainable resource extraction. However, critical knowledge gaps remain regarding viral ecology, horizontal gene transfer, eukaryotic diversity, and climate change impacts. We emphasize that hot springs merit renewed interdisciplinary attention as model systems for understanding extremophile physiology, early life evolution, and the development of nature-based biotechnological solutions. Realizing their full potential requires balanced management strategies that preserve ecosystem integrity while enabling responsible utilization of these irreplaceable geobiological resources.

The previous discovery of genomes of Polinton-like viruses (PLVs) associated with viruses of Chrysochromulina parva stimulated this research to determine the biological nature of these putative viral hyperparasites. Purification of C. parva viruses to enable co-infection experiments led to the discovery of a previously unknown virus, CpV-BQ3, which, based on sequence information and electron microscopy, is a species of Tethysvirus, a genus within the Megaviricetes. Purification and TEM imaging of CpV-PLV Moe revealed naked icosahedral particles morphologically similar to other cultivated virophages and PLVs. Mixed-infection experiments with the putative Polinton-like virus CpV-PLV Moe demonstrated that CpV-BQ3 supports its replication, whereas the putative Phycodnavirus CpV-BQ1 does not. Further, experimental infections with differing proportions of the Moe and its helper virus CpV-BQ3 revealed a dose-effect whereby high levels of Moe had a greater negative impact on BQ3 replication compared to lower levels. Conversely, high levels of Moe relative to BQ3 provided greater protection for C. parva, allowing enhanced cell survival, whereas low doses of Moe did not prevent cell lysis. Overall, the results of this study demonstrated the intimate relationship of CpV-PLV Moe with the newly discovered virus, CpV-BQ3, and C. parva, and illustrate the complex ecology of algal viruses.

Studying airborne viruses in remote environments like the sub-Antarctic island of South Georgia offers key insights into viral ecology, diversity, and their role in shaping ecosystems through microbial and nutrient interactions. We analyzed airborne viral community composition at two sites in South Georgia. Sampling took place using multiple methodologies, with the data produced subjected to viral metagenomics. The Coriolis μ device (wet collection) was the most effective, yielding 30 viral scaffolds. Two-thirds of the scaffolds were only obtained from the coastal location, indicating that location influences airborne viral diversity. Protein-based clustering of 39 viral operational taxonomic units (vOTUs) revealed similarities of 15 with known marine viruses, suggesting oceanic influence on the airborne viral community. Protein homologs related to UV damage protection and photosynthesis from two airborne vOTUs were widely distributed across major oceans, suggesting their potential role in supporting the resilience of marine microorganisms under changing climate conditions. Some vOTUs had protein similarities to viruses infecting extremophiles, indicating viral adaptations to harsh environments. This study provides a baseline for understanding the complexity and sustainability of airborne viral communities in remote ecosystems. It underscores the need for continued monitoring to assess how these communities respond to shifting atmospheric and ecological conditions.

Grassland ecosystems depend on soil- and plant-associated microbiomes that regulate nutrient cycling, soil structure formation, plant health, and stress tolerance. This review synthesizes recent progress on how grassland microbiomes are assembled across rhizosphere, endosphere, and bulk soil niches, and how degradation drivers (e.g., overgrazing, drought, salinization, and nutrient enrichment) disrupt microbial diversity, network stability, and functional guilds, often shifting communities toward reduced mutualist capacity and greater disease risk. We then evaluate restoration strategies that aim to re-establish beneficial microbial functions through practices such as organic amendments, inoculation with mycorrhizae or plant growth-promoting microbes, and management approaches that promote habitat recovery and microbial recolonization. Despite rapid advances in sequencing and observational studies, major gaps remain: (i) limited causal evidence linking microbiome changes to process rates (e.g., nitrification, phosphorus mobilization) across field gradients; (ii) underrepresentation of soil viral ecology and its consequences for microbial regulation and ecosystem function; (iii) inconsistent persistence and context-dependence of introduced inoculants; and (iv) a lack of standardized, outcome-oriented indicators for "restoration-ready" microbiomes. Future research should integrate multi-omics with process-based measurements and long-term field experiments, develop locally adapted microbial consortia with monitoring of non-target effects, and strengthen risk assessment and governance frameworks to enable safe, scalable microbiome-informed grassland restoration under global change.

Newcastle disease virus is an important poultry disease worldwide, affecting almost all bird species with significant losses usually associated with chickens. Non-chicken bird species have a role to play in the ecology of Newcastle disease virus (NDV) as they are able to serve as reservoirs that can contribute to viral transmission across bird’s species. In this study, the hemagglutination Inhibition test was used to investigate the serostatus of antibodies to NDV in non-chicken birds in Makurdi metropolis. The overall serostatus of anti-NDV antibodies in these bird species was found to be 29.05%, with species-specific prevalence rates of 51.2%, 7.3%, 34.8%, 12%, and 0% in Turkeys, Pigeons, Ducks, Guinea fowl, and Doves respectively. This study has added to the existing understanding of the seroprevalence and role of non-chicken birds in the epidemiology of NDV, particularly in the Makurdi , and underscores the need for region-specific surveillance and intervention measures.

BackgroundSevere Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infects many species, including companion animals. Monitoring changes in pet seropositivity rate provides insight into viral circulation at the human–animal interface. This study assessed SARS-CoV-2 seropositivity rate in dogs, cats, and rabbits in Poland between 2022 and 2025, focusing on demographic and time-related factors.MethodsA total of 1037 serum samples were collected from dogs (n = 611), cats (n = 385), and rabbits (n = 41) in nine Polish provinces. Antibodies against SARS-CoV-2 were detected using a multispecies nucleocapsid-based ELISA. Data on sampling year, species, location, age and gender were analysed. Seropositivity rate estimates with 95% confidence intervals were calculated using the Wilson score method. Associations were tested with Fisher’s exact test, and multivariable logistic regression was applied to assess predictors of seropositivity, including species, year, and age.ResultsThe overall seropositivity rate was 5.1% (53/1037; 95% CI: 3.93–6.62). Species-specific prevalence was 6.75% in cats (26/385; 95% CI: 4.65–9.71) and 4.42% in dogs (27/611; 95% CI: 3.05–6.35), while all rabbit samples were negative (0/41; 95% CI: 0.00-8.60). No significant temporal trend was observed across the study period, although prevalence was higher in 2024–2025 compared with 2022–2023. The proportion of seropositive animals was slightly higher in cats than in dogs (OR = 0.62 for dogs vs. cats, p = 0.096). Age was the strongest predictor: animals aged 4–7 years showed the highest seropositivity rate (7.98%, 19/238; OR = 3.94 compared to 0–3 years, p = 0.004). No significant associations were found with gender or geographic region.ConclusionsThis study demonstrates that cats and dogs in Poland have been exposed to SARS-CoV-2, with seropositivity rate levels consistent with international reports. Cats were more frequently seropositive than dogs, and middle-aged animals had the highest likelihood of exposure, reflecting cumulative contact opportunities during peak human transmission. Rabbits did not show evidence of past infection, suggesting negligible involvement in viral ecology under natural conditions. These findings support the role of pets as sentinels of community transmission and highlight the importance of continued One Health surveillance.

Anthropogenic-driven climate change is accelerating permafrost thaw, threatening to release vast carbon stores through increased microbial activity. While microbial roles are increasingly studied, the contributions of viruses remain largely unexplored, in part due to soil-associated technical challenges that have hindered their detection and characterization. Here, we applied an optimized virion enrichment workflow along a permafrost thaw gradient, identifying 9,963 viral populations (vOTUs), including single- and double-stranded DNA viruses, with 99.9% novelty compared to other soils. Hosts were predicted for 38% of vOTUs, spanning nine archaeal, and 36 bacterial phyla, 22% of which were linked to metagenome-assembled genomes, including key carbon-cycling taxa. Genomic analyses revealed 811 putative auxiliary metabolic genes (AMGs) from 658 vOTUs, nearly half involved in carbon processing. These included 59 glycoside hydrolases (GH) across nine GH families, 45 for monosaccharide degradation, and seven involved in short-chain fatty acid and C1 metabolism, linking viruses to both early and late stages of carbon turnover. Additionally, six vOTUs carried racD, which may stabilize microbial necromass and promote long-term carbon storage. Viral and AMG functional diversity increased with thaw stage, indicating that viruses might participate in a broadening range of microbial metabolic processes as permafrost thaws. These findings expand our understanding of virus contributions in microbial carbon processing and suggest their important role in deciphering soil carbon fate under changing climate conditions.

Peatlands hold up to one-third of Earth’s soil carbon but are increasingly turning from being carbon sinks to becoming carbon sources due to human impacts. Restoration efforts aim to reverse this trend, but viral influences on peatland recovery remain unclear, despite viruses being potent regulators of microbiomes and ecosystem function. Here we sequenced soil metagenomes to study viral communities across seven UK peatlands, each encompassing areas representing three peatland ecosystem health statuses: natural, damaged and restored. We found that viral diversity and community structure were shaped by both geography and ecosystem health. Viruses were geographically widespread, yet exhibited ecosystem health-specific endemism and functional adaptation, highlighting their sensitivity to restoration. Virus–host dynamics ranged from stable ‘piggyback-the-winner’ relationships to decoupled dynamics in those infecting keystone aerobes, sulfate reducers, carbohydrate degraders and fermenters. These findings position viruses as dynamic drivers of peatland ecosystem recovery and could unlock pathways to bolster carbon retention and accelerate climate mitigation.

Life of giant phages The Life of Giant Phages (GIAPHAGE) project is focused on revealing the unknown biology and ecology of large bacterial viruses, phages, using a unique set of isolates. It also aims to clarify how abundant large phages are and what role they play in the environment. GIAPHAGE started at the end of 2023 and is funded by a European Research Council Starting Grant.

Viruses play a crucial role in shaping microbial communities and global biogeochemical cycles, yet their vast genetic diversity remains underexplored. Next-generation sequencing technologies allow untargeted profiling of metagenomes from viral communities (viromes). However, existing workflows often lack modularity, flexibility, and seamless integration with other microbiome analysis platforms. Here, we introduce “ViromeXplore,” a set of modular Nextflow workflows designed for efficient virome analysis. ViromeXplore incorporates state-of-the-art tools for contamination estimation, viral sequence identification, taxonomic assignment, functional annotation, and host prediction while optimizing computational resources. The workflows are containerized using Docker and Singularity, ensuring reproducibility and ease of deployment. Additionally, ViromeXplore offers optional integration with QIIME 2 and MOSHPIT, facilitating provenance tracking and interoperability with microbiome bioinformatics pipelines. By providing a scalable, user-friendly, and computationally efficient framework, ViromeXplore enhances viral metagenomic analysis and contributes to a deeper understanding of viral ecology. ViromeXplore is freely available at https://github.com/rhernandvel/ViromeXplore.

ABSTRACTThe evolutionary, demographic, and phylogeographic histories of viral pathogens can be inferred from their genomic sequence data. Bayesian phylogeographic approaches, for example, can be used to reconstruct the spatial dynamics of pathogen transmission. Although a range of tools is available for evolutionary analyses of viral pathogens, these typically focus on specific stages of the workflow, leaving a need for an integrated framework. We introduce VirPhyKit, a toolkit that integrates 12 specialized modules through an intuitive point‐and‐click interface. VirPhyKit streamlines key tasks in phylogeographic analysis, including sequence curation, spatiotemporal subsampling, migration pattern analysis, and molecular dating. Furthermore, it offers built‐in functionality to generate high‐quality figures that are suitable for publication. As a stand‐alone application supported on Windows and Linux operating systems, VirPhyKit promises to be a valuable resource for researchers studying viral ecology and evolution. The software and source code are available at https://github.com/BioEasy/VirPhyKit.

ABSTRACTViral‐mediated bacterial mortality and the prevalence of lysogeny are two key parameters for understanding the role of viral activity in aquatic ecosystems. The viral production assay is most commonly used to assess these parameters, with lytic and mitomycin C‐induced viral production rates prevalently extracted using the linear regression or increment‐based (VIPCAL) approach. A literature survey shows that 64% of the 89 viral production studies used the linear regression approach for lytic and 48% employed VIPCAL for lysogenic viral production rates. Our comparative evaluation highlights significant differences between these two approaches of estimating viral production rates. To refine estimations, we enhanced VIPCAL to VIPCAL‐SE by incorporating standard error of the means to rigorously identify maxima–minima pairs, accounting for biological and ecological variabilities between replicates. We also included a bacterial net generation time endpoint to reduce estimation bias due to potential secondary infections, particularly relevant in more productive ecosystems. VIPCAL‐SE is now available as a part of the viralprod R package and provides an opportunity for further standardisation in the field of aquatic viral ecology.

Protocol for virome characterization in low-volume respiratory samples from broiler chickens.

Metagenomic survey reveals Volzhskoe tick virus in Hyalomma ticks for the first time in western Europe, North-Eastern Spain

Viruses are the most abundant biological entities on Earth, yet their global diversity remains largely unexplored. Here, we present VIRE, a comprehensive resource comprising over 1.7 million high- and medium-quality viral genomes recovered from >100 000 publicly available metagenomes derived from samples that cover diverse ecosystems, including host-associated, aquatic, terrestrial, and anthropogenic environments. Using a unified and scalable pipeline, we systematically assembled viral genomes and provided detailed information on genome completeness, taxonomic classification, predicted lifestyle, and host assignment based on CRISPR spacer matches. VIRE contains >89 million predicted viral open reading frames, as well as detailed functional annotations derived from multiple databases. Importantly, VIRE is seamlessly integrated with related microbiome resources such as SPIRE (https://spire.embl.de) and Metalog (https://metalog.embl.de), enabling users to jointly explore viral genomes, metagenome-assembled genomes, and associated environmental or clinical metadata. Accessible at https://vire.embl.de, VIRE provides an open-access, scalable platform for investigating viral diversity, evolution, and ecology on a planetary scale.

Accurately characterising the human gut virome is critical to understanding virus-microbiome-host interactions. However, widely used methods introduce biases that complicate data interpretation and limit cross-study comparability. For instance, multiple-displacement amplification (MDA) preferentially amplifies single-stranded DNA viruses, while total metagenomes are dominated by non-viral sequences, reducing viral signal. These traditional methods have not been systematically compared to viral size-fraction metagenomes (viromes) prepared without MDA. To address this, we applied four common methods for characterising human gut viral community composition (total metagenomes, viromes with/without DNase treatment (to remove free DNA), and MDA viromes) to a human stool sample, with technical triplicates for each approach. MDA biased viral community composition to a shocking degree: Microviridae formed ~90% of MDA viromes compared to just 2% of non-MDA viromes. Removing ssDNA viruses from data analyses substantially reduced, but did not eliminate, MDA bias. Metagenomes were enriched for putative temperate phages and predicted Bacillota-phages, whereas predicted Bacteroidetes-phages dominated all viromes, suggesting that metagenomes and viromes select for different populations within the total viral community. DNase treatment had little-to-no effect on virome richness or community composition. This proof-of-principle experiment demonstrates that preparatory methods for viral community analysis can lead to substantially different conclusions from the same faecal sample, and we provide a comprehensive omic data analysis framework for comparing laboratory methodologies for viral ecology. With sufficient DNA yields now easily achievable from human gut viromes without the use of MDA, our results suggest that this biased amplification method should be avoided in human gut virome studies.

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 outperforms other homology- and language model-based approaches for relating viral genomes based on shared protein content. Further, PST demonstrates 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.