Main menu

Automated strain separation in low-complexity metagenomes using long reads


High-throughput short-read metagenomics has enabled large-scale species-level analysis and functional characterization of microbial communities. Microbiomes often contain multiple strains of the same species, and different strains have been shown to have important differences in their functional roles. Despite this, strain-level resolution from metagenomic sequencing remains challenging. Recent advances on long-read based methods enabled accurate assembly of bacterial genomes from complex microbiomes and an as-yet-unrealized opportunity to resolve strains.

Here we present Strainberry, a metagenome assembly method that performs strain separation in single-sample low-complexity metagenomes and that relies uniquely on long-read data. We benchmarked Strainberry on mock communities and showed it consistently produces strain-resolved assemblies with near-complete reference coverage and 99.9% base accuracy. We also applied Strainberry on real datasets for which it improved assemblies generating 27-89% additional genomic material than conventional metagenome assemblies on individual strain genomes.

Our results hence demonstrate that strain separation is possible in low-complexity microbiomes using a single regular long read dataset. We show that Strainberry is also able to refine microbial diversity in a complex microbiome, with complete separation of strain genomes. We anticipate this work to be a starting point for further methodological improvements aiming to provide better strain-resolved metagenome assemblies in environments of higher complexities.

Authors: R. Vicedomini, C. Quince, A. E. Darling, R. Chikhi

入门指南

购买 MinION 启动包 Nanopore 商城 测序服务提供商 全球代理商

纳米孔技术

订阅 Nanopore 更新 资源库及发表刊物 什么是 Nanopore 社区

关于 Oxford Nanopore

新闻 公司历程 可持续发展 领导团队 媒体资源和联系方式 投资者 合作者 在 Oxford Nanopore 工作 职位空缺 商业信息 BSI 27001 accreditationBSI 90001 accreditationBSI mark of trust
Chinese flag