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6 recordsLinked to original sources
PubMed2026

ViralQC: a tool for assessing completeness and contamination of predicted viral contigs.

MOTIVATION: Viruses represent the most abundant biological entities on Earth, playing vital roles in diverse ecosystems. Cataloging viruses across various environments is essential for understanding their properties and functions. Metagenomic sequencing has emerged as the most comprehensive method for virus discovery. However, distinguishing viral sequences from the vast background of microbial organisms in metagenomic data remains a significant challenge. Existing tools experience varying degrees of false positive rates due to noise in sequencing and assembly, and the integration of proviruses into microbial genomes. This highlights the urgent need for an accurate and efficient method to evaluate the quality of viral contigs. RESULTS: To address these challenges, we introduce ViralQC, a tool designed to assess the quality of viral contigs or bins. ViralQC identifies microbial contamination within putative viral sequences using an ensemble framework powered by DNA and protein foundation models and estimates completeness by analyzing protein organization. We evaluated ViralQC on multiple datasets and compared its performance against the state-of-the-art tool, CheckV. Leveraging both DNA and protein foundation models, ViralQC achieves higher sensitivity on contamination detection for contigs longer than 10 kbp while maintaining comparable accuracy. Additionally, ViralQC delivers more accurate estimation on contigs with completeness > 50%. AVAILABILITY: The source code of ViralQC is available via: https://github.com/ChengPENG-wolf/ViralQC.

Software↗
PubMed2025

Synthetic community Hi-C benchmarking provides a baseline for virus-host inferences.

Microbiomes influence diverse ecosystems, and viruses increasingly appear to impose key constraints. While viromics has expanded genomic catalogs, host identification for these viruses remains challenging due to the limitations in scaling cultivation-based approaches and the uncertain reliability and relative low resolution of in silico predictions - particularly for understudied viral taxa. Towards this, Hi-C proximity ligation uses sequenced, cross-linked virus and host genomic fragments to infer virus-host linkages and has now been applied in at least ten studies. However, its accuracy remains unknown. Here we assess Hi-C performance in recovering virus-host interactions using synthetic communities (SynComs) composed of four marine bacterial strains and nine phages with known interactions and then apply optimized bioinformatic protocols to natural soil samples. In SynComs, standard Hi-C sample preparations and analyses showed poor normalized contact score performance (26% specificity, 100% sensitivity, incorrect matches up to class level) that could be dramatically improved by Z-score filtering (Z ≥ 0.5, 99% specificity), though at reduced sensitivity (62% down from 100%). Detection limits were established as reproducibility was poor below minimal phage abundances of 105 PFU/mL. Applying optimized bioinformatic protocols to natural soil samples, we compared virus-host linkages inferred from proximity-ligated Hi-C sequencing with predictions generated by in silico homology-based and machine learning-based bioinformatic approaches. Prior to Z-score thresholding, agreement was relatively high at the phylum to family levels (72%), but not at the genus (43%) or species (15%) levels. Z-score thresholding reduced sensitivity (only 34% of predictions were retained), with only modest improvements in congruence with bioinformatic methods (48% or 18% at genus or species levels, respectively). Regardless, this led to 79 genus-level-congruent virus-host linkages and 293 new ones revealed by Hi-C alone - i.e., providing many new virus-host interactions to explore in already well-studied climate-critical soils. Overall, these findings provide empirical benchmarks and methodological guidelines to improve the accuracy and reliability of Hi-C for virus-host linkage studies in complex microbial communities.

Genomics↗
PubMed2025

Benchmarking with synthetic communities provides a baseline for virus-host inferences from Hi-C proximity linking.

Microbiomes influence diverse ecosystems, and viruses increasingly appear to impose key constraints. While viromics has expanded genomic catalogs, host identification for these viruses remains challenging due to the limitations in scaling cultivation-based approaches and the uncertain reliability and relative low resolution of in silico predictions - particularly for understudied viral taxa. Towards this, Hi-C proximity ligation uses sequenced, cross-linked virus and host genomic fragments to infer virus-host linkages and has now been applied in at least 10 studies. However, its accuracy remains unknown. Here we assess Hi-C performance in recovering virus-host interactions using synthetic communities (SynComs) composed of four marine bacterial strains and nine phages with known interactions and then apply optimized bioinformatic protocols to natural soil samples. In SynComs, standard Hi-C sample preparations and analyses showed poor normalized contact score performance (26% specificity, 100% sensitivity, incorrect matches up to class level) that could be dramatically improved by Z-score filtering (Z ≥ 0.5, 99% specificity), though at reduced sensitivity (62% down from 100%). Detection limits were established as reproducibility was poor below minimal phage abundances of 105 PFU/mL. Applying optimized bioinformatic protocols to natural soil samples, we compared virus-host linkages inferred from proximity-ligated Hi-C sequencing with predictions generated by in silico homology-based and machine learning-based bioinformatic approaches. Prior to Z-score thresholding, agreement was relatively high at the phylum to family levels (72%), but not at the genus (43%) or species (15%) levels. Z-score thresholding reduced sensitivity (only 34% of predictions were retained), with only modest improvements in congruence with bioinformatic methods (48% or 18% at genus or species levels, respectively). Regardless, this led to 79 genus-level-congruent virus-host linkages and 293 new ones revealed by Hi-C alone, i.e., providing many new virus-host interactions to explore in already well-studied climate-critical soils. Overall, these findings provide empirical benchmarks and methodological guidelines to improve the accuracy and reliability of Hi-C for virus-host linkage studies in complex microbial communities.

Benchmarking↗
PubMed2025

A comprehensive reference catalog of human skin DNA virome reveals novel viral diversity and microenvironmental influences.

UNLABELLED: Human skin serves as a dynamic habitat for a diverse microbiome, including a complex array of viruses whose diversity and roles are not fully understood. A total of 2,760 skin metagenomes from 6 published skin studies were collected. A skin virome catalog was constructed using standard methods in the viromics field. Viral characteristics were identified through cross-cohort meta-analysis and used to characterize viral features across different skin environments. We identified 20,927 viral sequences, which clustered into 2,873 viral operational taxonomic units (vOTUs), uncovering a substantial breadth of viral diversity on human skin. The results also highlight significant differences in viral communities that are associated with varying skin microenvironments. The oily skin is enriched in Papillomaviridae, the dry skin area is enriched in Autographiviridae and Inoviridae, and the moist skin is enriched in Herelleviridae. We also investigated the relationship between bacteriophages and bacteria on the skin surface. We found that skin bacteria such as Pseudomonas, Klebsiella, and Staphylococcus are predicted to be infected by phages from the class Caudoviricetes. This comprehensive skin DNA viral catalog significantly advances our understanding of the virome's role within the skin ecosystem. IMPORTANCE: This study presents a comprehensive reference catalog of the human skin DNA virome, constructed from 2,760 metagenomic datasets collected globally. It identified 20,927 viral sequences, with 90.85% representing previously unknown viruses, greatly expanding our understanding of skin viral diversity. The findings reveal significant differences in viral communities between distinct skin microenvironments (oily, dry, and moist) and highlight close interactions between bacteriophages and their bacterial hosts, suggesting a potential role for the virome in maintaining microbial balance and skin health. This extensive skin viral catalog constitutes a crucial resource for future epidemiological and therapeutic research, potentially facilitating the development of novel phage therapies and diagnostic markers for skin disorders.

Humans↗
PubMed2026

The factory enters the fray: how mitochondrial protein trafficking shapes the host response to infection.

Beyond textbook functions in homeostatic metabolism, mitochondria are now recognized as central coordinators of cell-intrinsic and cell-extrinsic immune responses to infection. Directed trafficking of proteins and other molecules between mitochondria and the rest of the cell underlies a growing catalog of these activities. Some are pro-host; others are antagonized by viral effectors or co-opted by viruses entirely. How host and viral factors rewire the mitochondrial proteome during infection to shape these outcomes remains incompletely understood. The evolutionary history of this system adds another dimension: mitochondria retain biochemical signatures of their α-proteobacterial endosymbiotic origin, and ongoing co-evolution between viral, host, and mitochondrial genomes continues to shape the proteins that traffic to and from the organelle. Using published examples, we highlight general principles, mechanisms, and consequences of host and viral protein localization to and from the mitochondria. To support discovery, we present integrated gene lists identifying host mitochondrial factors with evidence for type I interferon stimulation, interactions with viral proteins, and signatures of positive selection. Together, these resources and the principles within offer a framework for understanding mitochondria not as passive metabolic machinery but as actively contested cellular territory whose protein composition is continuously negotiated between the host and the pathogen.

adaptation↗
PubMed2026

Elevation-structured viral ecological strategies along glacier-fed rivers on the Qinghai-Tibet Plateau.

The Qinghai-Tibet Plateau, a climate-vulnerable source of Asia's major rivers, harbors underexplored viral communities critical to ecosystem functions. By integrating 597 metagenomes from the Yangtze, Yellow, Lancang, and Yarlung Tsangpo rivers with 85 public available glacial metagenomes (Tibetan Glacier Genome and Gene catalog), we built the Glacier-to-River Virome Catalogue, encompassing 36,358 vOTUs and 897,250 viral protein clusters, to decode viral adaptation and ecological influence across elevation gradients. Our results reveal that high-altitude conditions favor viruses with elevated Guanine-Cytosine content, larger genomes and more cold-adaptation genes. A central finding is a systematic viral lifestyle shift from temperate in glaciated regions to lytic viruses downstream, accompanied with decline of pathogens carrying antibiotic resistance genes along the glacier-to-river gradients. Further, viral auxiliary metabolic genes transition from glacier nutrient scavenging (e.g., nitrogen and sulfur transporters) to downstream mineralization processes (e.g., denitrification) in plains highlights their role in biogeochemical cycling. These findings position viruses as pivotal regulators of microbial community structural and functional dynamics to glacier-to-river gradient change and biogeochemistry in the Qinghai-Tibet Plateau, providing critical insights into climate response in vulnerable Asian water towers.

Ice Cover↗