Suppr超能文献

原位菌株的宏基因组生长速率推断

Metagenomic growth rate inferences of strains in situ.

作者信息

Emiola Akintunde, Zhou Wei, Oh Julia

机构信息

The Jackson Laboratory for Genomic Medicine, Farmington, CT 06032, USA.

出版信息

Sci Adv. 2020 Apr 22;6(17):eaaz2299. doi: 10.1126/sciadv.aaz2299. eCollection 2020 Apr.

Abstract

We developed a method for strain-level metagenomic estimation of growth rate (SMEG) for inferring growth rates of bacterial subspecies, or strains, from complex metagenomic samples. We applied our method, which is based on both reference strains and de novo approaches, to different gut metagenomic datasets, accurately identifying an outbreak-associated strain and a previously unidentified association of an strain in cancer immunotherapy responders. SMEG resolves strain-specific growth rates from mixtures of commensal or pathogenic strains to provide new insights into microbial interactions and disease associations at the strain level. SMEG is available for download at https://github.com/ohlab/SMEG.

摘要

我们开发了一种用于从复杂宏基因组样本中推断细菌亚种或菌株生长速率的菌株水平宏基因组生长速率估计方法(SMEG)。我们将基于参考菌株和从头开始方法的该方法应用于不同的肠道宏基因组数据集,准确识别出与一次疫情相关的菌株以及癌症免疫治疗应答者中一种先前未被识别的菌株关联。SMEG 从共生或致病菌株混合物中解析出菌株特异性生长速率,以在菌株水平上为微生物相互作用和疾病关联提供新见解。可在 https://github.com/ohlab/SMEG 上下载 SMEG。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f8fb/7176420/681c0b67bf6d/aaz2299-F1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验