Evidence map›Paper›PMID 39707560›Full record

ArticleMicrobiome2024

Complementary insights into gut viral genomes: a comparative benchmark of short- and long-read metagenomes using diverse assemblers and binners.

Huarui Wang, Chuqing Sun, Yun Li, Jingchao Chen, Xing-Ming Zhao, Wei-Hua Chen

Abstract readComparative Study
In one paragraph

Article in Microbiome, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Huarui WangKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Department of Bioinformatics and Systems Biology, Center for Artificial Intelligence Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Chuqing SunKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Department of Bioinformatics and Systems Biology, Center for Artificial Intelligence Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Yun LiKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Department of Bioinformatics and Systems Biology, Center for Artificial Intelligence Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Jingchao ChenKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Department of Bioinformatics and Systems Biology, Center for Artificial Intelligence Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China.
Xing-Ming ZhaoDepartment of Neurology, Institute of Science and Technology for Brain-Inspired Intelligence, Zhongshan Hospitaland, Fudan University , Shanghai, 200433, China. xmzhao@fudan.edu.cn.
Wei-Hua ChenKey Laboratory of Molecular Biophysics of the Ministry of Education, Hubei Key Laboratory of Bioinformatics and Molecular Imaging, Department of Bioinformatics and Systems Biology, Center for Artificial Intelligence Biology, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, Hubei, 430074, China. weihuachen@hust.edu.cn.

Funding

National Key Research and Development Program of China 2019YFA0905600National Key Research and Development Program of China 2020YFA0712403National Natural Science Foundation of China 32070660National Natural Science Foundation of China T2225015NNSF-VR Sino-Swedish Joint Research Programme 82161138017
6 · The paper itself

Abstract

backgroundMetagenome-assembled viral genomes have significantly advanced the discovery and characterization of the human gut virome. However, we lack a comparative assessment of assembly tools on the efficacy of viral genome identification, particularly across next-generation sequencing (NGS) and third-generation sequencing (TGS) data.

resultsWe evaluated the efficiency of NGS, TGS, and hybrid assemblers for viral genome discovery using 95 viral-like particle (VLP)-enriched fecal samples sequenced on both Illumina and PacBio platforms. MEGAHIT, metaFlye, and hybridSPAdes emerged as the optimal choices for NGS, TGS, and hybrid datasets, respectively. Notably, these assemblers recovered distinct viral genomes, demonstrating a remarkable degree of complementarity. By combining individual assembler results, we expanded the total number of nonredundant high-quality viral genomes by 4.83 ~ 21.7-fold compared to individual assemblers. Among them, viral genomes from NGS and TGS data have the least overlap, indicating the impact of data type on viral genome recovery. We also evaluated four binning methods, finding that CONCOCT incorporated more unrelated contigs into the same bins, while MetaBAT2, AVAMB, and vRhyme balanced inclusiveness and taxonomic consistency within bins.

conclusionsOur findings highlight the challenges in metagenome-driven viral discovery, underscoring tool limitations. We advocate for combined use of multiple assemblers and sequencing technologies when feasible and highlight the urgent need for specialized tools tailored to gut virome assembly. This study contributes essential insights for advancing viral genome research in the context of gut metagenomics. Video Abstract.

Indexed as

FecesGastrointestinal MicrobiomeGenome, ViralHigh-Throughput Nucleotide SequencingMetagenomeBenchmarkingHumansMetagenomicsSequence Analysis, DNAViromeViruses

Identifiers

PMID39707560
PMCPMC11660840

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.