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

作者：Wei Xue, Liu Zuo, Yaozhong Zhang, Waseem Raza, Yarong Li, Li Jiang, Tao Ye, Jun Qian, Alexandre Jousset, Fang‐Jie Zhao, Yangchun Xu, Fritz J. Sedlazeck, Qirong Shen, Gaofei Jiang, Zhong Wei · 发表于：Nature Communications · 年份：2025 · DOI：10.1038/s41467-025-64916-8 · 被引用次数：3 · 研究领域：Genomics and Phylogenetic Studies、Microbial Community Ecology and Physiology、Gut microbiota and health

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.