LorBin: efficient binning of long-read metagenomes by multiscale adaptive clustering and evaluation

Long-read sequencing has transformed metagenomics and improved the quality of metagenome-assembled genomes (MAGs). However, current binning methods struggle with identifying unknown species and managing imbalanced species distributions. Here, we present LorBin, an unsupervised binner specially designed to reconstruct MAGs in natural microbiomes. LorBin deploys a two-stage multiscale adaptive DBSCAN and BIRCH clustering with evaluation decision models using single-copy genes to maximize MAG recovery. LorBin outperforms six competing binners in both simulated and real microbiomes, including oral, gut, and marine samples. LorBin generated 15-189% more high-quality MAGs with high serendipity and identified 2.4-17 times more novel taxa than state-of-the-art binning methods. Together, LorBin is a promising long-read metagenomic binner for accessing species-rich samples containing unknown taxa and is efficient at retrieving more complete genomes from imbalanced natural microbiomes.

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Publication Details

Journal
Nature Communications
Published
2025-10-24
DOI
https://doi.org/10.1038/s41467-025-64916-8
Citations
1
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
0.81

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article

LorBin: efficient binning of long-read metagenomes by multiscale adaptive clustering and evaluation

Gaofei Jiang, Alexandre Jousset, Zhong Wei, Fritz J. Sedlazeck et al.
1 citations
Nature Communications
Genomics and Phylogenetic Studies
0.81
article

LorBin: efficient binning of long-read metagenomes by multiscale adaptive clustering and evaluation

Gaofei Jiang, Alexandre Jousset, Zhong Wei, Fritz J. Sedlazeck, Yangchun Xu, Fang‐Jie Zhao, Qirong Shen, Waseem Raza, Yaozhong Zhang, Yarong Li, Tao Ye, Jun Qian, Liu Zuo, Li Jiang, Wei Xue
article en
1 citations

Abstract

Long-read sequencing has transformed metagenomics and improved the quality of metagenome-assembled genomes (MAGs). However, current binning methods struggle with identifying unknown species and managing imbalanced species distributions. Here, we present LorBin, an unsupervised binner specially designed to reconstruct MAGs in natural microbiomes. LorBin deploys a two-stage multiscale adaptive DBSCAN and BIRCH clustering with evaluation decision models using single-copy genes to maximize MAG recovery. LorBin outperforms six competing binners in both simulated and real microbiomes, including oral, gut, and marine samples. LorBin generated 15-189% more high-quality MAGs with high serendipity and identified 2.4-17 times more novel taxa than state-of-the-art binning methods. Together, LorBin is a promising long-read metagenomic binner for accessing species-rich samples containing unknown taxa and is efficient at retrieving more complete genomes from imbalanced natural microbiomes.

Nature CommunicationsVol. 16(1)
Chinese Academy of Tropical Agricultural Sciences (CN), Nanjing Agricultural University (CN), Baylor College of Medicine (US), Genedata (Switzerland) (CH), Shanghai Genon Biological Products (China) (CN), Shanghai CASB Biotechnology (China) (CN), Microsoft Research Asia (China) (CN)
National Natural Science Foundation of China, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 22%
Genomics and Phylogenetic Studies
0.81
DOIOpen Access PDFOpenAlex
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