Virus classification for viral genomic fragments using PhaGCN2

Jiang, Jing‐Zhe; Yuan, Wen-Guang; Shang, Jiayu; Shi, Ying-Hui; Yang, Liling; Liu, Min; Zhu, Peng; Jin, Tao; Sun, Yanni; Yuan, Lihong

doi:10.1093/bib/bbac505

Cited by 40 publications

(27 citation statements)

References 28 publications

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“…Then, cytoscape v3.8.0 was used to visualize the network ( 77 ). Considering the major revisions of viral taxonomy in ICTV ( 78 , 79 ), the vOTUs were further annotated using PhaGCN v2.1 with the latest ICTV classification ( 80 , 81 ).…”

Section: Methodsmentioning

confidence: 99%

Tundra Soil Viruses Mediate Responses of Microbial Communities to Climate Warming

Fan

Cornell

et al. 2023

mBio

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Section: Methodsmentioning

confidence: 99%

Tundra Soil Viruses Mediate Responses of Microbial Communities to Climate Warming

Fan

Cornell

et al. 2023

mBio

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“…Taxonomic assignment of viral contigs was performed using PhaGCN2 based on the latest ICTV classification tables [59]. Reference viruses were obtained from the RefSeq viral database (v216, released in Jan. 2023).…”

Section: Viral Contig Identification Taxonomic Classification and Fun...mentioning

confidence: 99%

Mesophilic and thermophilic viruses are associated with nutrient cycling during hyperthermophilic composting

Liao

Liu

et al. 2023

The ISME Journal

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While decomposition of organic matter by bacteria plays a major role in nutrient cycling in terrestrial ecosystems, the significance of viruses remains poorly understood. Here we combined metagenomics and metatranscriptomics with temporal sampling to study the significance of mesophilic and thermophilic bacteria and their viruses on nutrient cycling during industrial-scale hyperthermophilic composting (HTC). Our results show that virus-bacteria density dynamics and activity are tightly coupled, where viruses specific to mesophilic and thermophilic bacteria track their host densities, triggering microbial community succession via top-down control during HTC. Moreover, viruses specific to mesophilic bacteria encoded and expressed several auxiliary metabolic genes (AMGs) linked to carbon cycling, impacting nutrient turnover alongside bacteria. Nutrient turnover correlated positively with virus–host ratio, indicative of a positive relationship between ecosystem functioning, viral abundances, and viral activity. These effects were predominantly driven by DNA viruses as most detected RNA viruses were associated with eukaryotes and not associated with nutrient cycling during the thermophilic phase of composting. Our findings suggest that DNA viruses could drive nutrient cycling during HTC by recycling bacterial biomass through cell lysis and by expressing key AMGs. Viruses could hence potentially be used as indicators of microbial ecosystem functioning to optimize productivity of biotechnological and agricultural systems.

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“…To further investigate specific sequences that were exclusively predicted by different tools, we taxonomically classified them using PhaGCN2.0 (v2.0) 72 . Gene annotation plots were created by a custom python script, after searching the translated amino acid sequences against the PHROG (v4) 73 HMM profile database using HHsearch from the HH-suite (v.3.3.0) 74 .…”

Section: Additional Contigs Validationmentioning

confidence: 99%

Benchmarking Bioinformatic Virus Identification Tools Using Real-World Metagenomic Data across Biomes

Pappas

Wijesekara

et al. 2023

Preprint

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As most viruses remain uncultivated, metagenomics is currently the main method for virus discovery. Detecting viruses in metagenomic data is not trivial. In the past few years, many bioinformatic virus identification tools have been developed for this task, making it challenging to choose the right tools, parameters, and cutoffs. As all these tools measure different biological signals, and use different algorithms and training/reference databases, it is imperative to conduct an independent benchmarking to give users objective guidance. We compared the performance of ten state-of-the-art virus identification tools in thirteen modes on eight paired viral and microbial datasets from three distinct biomes, including a new complex dataset from Antarctic coastal waters. The tools had highly variable true positive rates (0 - 68%) and false positive rates (0 - 15%). PPR-Meta best distinguished viral from microbial contigs, followed by DeepVirFinder, VirSorter2, and VIBRANT. Different tools identified different subsets of the benchmarking data and all tools, except for Sourmash, found unique viral contigs. Tools performance could be improved with adjusted parameter cutoffs, indicating that adjustment of parameter cutoffs before usage should be considered. Together, our independent benchmarking provides guidance on choices of bioinformatic virus identification tools and gives suggestions for parameter adjustments for viromics researchers.

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Virus classification for viral genomic fragments using PhaGCN2

Cited by 40 publications

References 28 publications

Tundra Soil Viruses Mediate Responses of Microbial Communities to Climate Warming

Tundra Soil Viruses Mediate Responses of Microbial Communities to Climate Warming

Mesophilic and thermophilic viruses are associated with nutrient cycling during hyperthermophilic composting

Benchmarking Bioinformatic Virus Identification Tools Using Real-World Metagenomic Data across Biomes

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