Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy

TLDR

Microbial communities are essential to ecosystem function, yet current binning methods often fail to produce sufficient high‑quality, complete genomes, and their performance varies across samples and environments. The study aims to improve metagenomic binning by introducing DAS Tool. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tool applied to a constructed community generated more accurate bins than any automated method, and when applied to environmental and host‑associated samples of different complexity, it recovered substantially more near‑complete genomes, including previously unreported lineages, than any single binning method alone, thereby greatly advancing genome‑centric analyses of ecosystems.

Abstract

Microbial communities are critical to ecosystem function. A key objective of metagenomic studies is to analyse organism-specific metabolic pathways and reconstruct community interaction networks. This requires accurate assignment of assembled genome fragments to genomes. Existing binning methods often fail to reconstruct a reasonable number of genomes and report many bins of low quality and completeness. Furthermore, the performance of existing algorithms varies between samples and biotopes. Here, we present a dereplication, aggregation and scoring strategy, DAS Tool, that combines the strengths of a flexible set of established binning algorithms. DAS Tool applied to a constructed community generated more accurate bins than any automated method. Indeed, when applied to environmental and host-associated samples of different complexity, DAS Tool recovered substantially more near-complete genomes, including previously unreported lineages, than any single binning method alone. The ability to reconstruct many near-complete genomes from metagenomics data will greatly advance genome-centric analyses of ecosystems.