ArticleFrontiers in genetics2019
MetaTOR: A Computational Pipeline to Recover High-Quality Metagenomic Bins From Mammalian Gut Proximity-Ligation (meta3C) Libraries.
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed.
- Phagocytosis of microbial symbionts supports embryonic nutrition in the sponge Halichondria panicea.Microbiome · 2026Article
- VirBinn improves viral genome binning from metagenomic Hi-C through graph diffusion.Bioinformatics (Oxford, England) · 2026Article
- Segmented filamentous bacteria are worldwide human gut commensals.Nature communications · 2026Article
- Benchmarking alignment strategies for Hi-C reads in metagenomic Hi-C data.Genome biology · 2026Article
- Abundance-activity decoupling in sulfur-cycling bacteria reflects viral infection types in meromictic lakes.The ISME journal · 2026Article
- Phages with a broad host range are common across ecosystems.Nature microbiology · 2025Article
- MetaHiCNet: a web server for normalizing and visualizing microbial Hi-C interaction networks.Nucleic acids research · 2025Article
- MetaCC allows scalable and integrative analyses of both long-read and short-read metagenomic Hi-C data.Nature communications · 2023Article
- Horizontal Gene Transfer of Antibiotic Resistance Genes in Biofilms.Antibiotics (Basel, Switzerland) · 2023Review
- ViralCC retrieves complete viral genomes and virus-host pairs from metagenomic Hi-C data.Nature communications · 2023Article
- Genome-centric analysis of short and long read metagenomes reveals uncharacterized microbiome diversity in Southeast Asians.Nature communications · 2022Article
- Introduction to the principles and methods underlying the recovery of metagenome-assembled genomes from metagenomic data.MicrobiologyOpen · 2022Review
- HAM-ART: An optimised culture-free Hi-C metagenomics pipeline for tracking antimicrobial resistance genes in complex microbial communities.PLoS genetics · 2022Article
- HiCBin: binning metagenomic contigs and recovering metagenome-assembled genomes using Hi-C contact maps.Genome biology · 2022Article
- Normalizing Metagenomic Hi-C Data and Detecting Spurious Contacts Using Zero-Inflated Negative Binomial Regression.Journal of computational biology : a journal of computational molecular cell biology · 2022Article
- MetaHiC phage-bacteria infection network reveals active cycling phages of the healthy human gut.eLife · 2021Article
- Hi-C Metagenomics in the ICU: Exploring Clinically Relevant Features of Gut Microbiome in Chronically Critically Ill Patients.Frontiers in microbiology · 2021Article
- Experimental approaches to tracking mobile genetic elements in microbial communities.FEMS microbiology reviews · 2020Review
- Accurate and complete genomes from metagenomes.Genome research · 2020Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Characterizing the complete genomic structure of complex microbial communities would represent a key step toward the understanding of their diversity, dynamics, and evolution. Current metagenomics approaches aiming at this goal are typically done by analyzing millions of short DNA sequences directly extracted from the environment. New experimental and computational approaches are constantly sought for to improve the analysis and interpretation of such data. We developed MetaTOR, an open-source computational solution that bins DNA contigs into individual genomes according to their 3D contact frequencies. Those contacts are quantified by chromosome conformation capture experiments (3C, Hi-C), also known as proximity-ligation approaches, applied to metagenomics samples (meta3C). MetaTOR was applied on 20 meta3C libraries of mice gut microbiota. We quantified the program ability to recover high-quality metagenome-assembled genomes (MAGs) from metagenomic assemblies generated directly from the meta3C libraries. Whereas nine high-quality MAGs are identified in the 148-Mb assembly generated using a single meta3C library, MetaTOR identifies 82 high-quality MAGs in the 763-Mb assembly generated from the merged 20 meta3C libraries, corresponding to nearly a third of the total assembly. Compared to the hybrid binning softwares MetaBAT or CONCOCT, MetaTOR recovered three times more high-quality MAGs. These results underline the potential of 3C-/Hi-C-based approaches in metagenomic projects.
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