基于宏基因组数据对菌群中低丰度细菌的生长速率进行原位测量
  • 生长速率指数(GRiD)可在超低测序覆盖度(0.2x)下测量宏基因组草图、分箱对应细菌的生长速率;
  • 与既有的iRep和PTR方法相比,GRiD的主要改进在于采用了额外的统计滤波器降低数据噪音,并使用dnaA和dif序列交叉验证预测结果;
  • 采用GRiD方法分别分析了牛皮癣、银屑病患者皮肤样本的宏基因组数据,发现了一些潜在能够保持持续生长的新物种(分箱);
  • GRiD-MG在此基础上实现了对宏基因组中对细菌生长速率的高通量测量;
  • 方法可通过Conda部署。
主编推荐语
高春辉
与现有的细菌生长速率测定软件相比,GRiD方法既不需要完整的基因组信息,也不需要微生物组成信息。由于其能够在极低测序覆盖度的条件下测量微生物生长速率,所以特别适合分析低丰度物种。点击查看另一个同类工具(查看文章)。
关键字
延伸阅读本研究的原文信息和链接出处,以及相关解读和评论文章。欢迎读者朋友们推荐!
图片

High throughput in situ metagenomic measurement of bacterial replication at ultra-low sequencing coverage

在极低测序覆盖度条件下基于宏基因组对细菌复制进行高通量测量

10.1038/s41467-018-07240-8

2018-11-23, Article

Abstract & Authors:展开

Abstract:收起
We developed Growth Rate InDex (GRiD) for estimating in situ growth rates of ultra-low coverage (>0.2×) and de novo-assembled metagenomes. Applying GRiD to human and environmental metagenomic datasets to demonstrate its versatility, we uncovered new associations with previously uncharacterized bacteria whose growth rates were associated with several disease characteristics or environmental interactions. In addition, with GRiD-MG (metagenomic), a high-throughput implementation of GRiD, we estimated growth dynamics of 1756 bacteria species from a healthy skin metagenomic dataset and identified a new Staphylococcus-Corynebacterium antagonism likely mediated by antimicrobial production in the skin. GRiD-MG significantly increases the ability to extract growth rate inferences from complex metagenomic data with minimal input from the user.

First Authors:
Akintunde Emiola

Correspondence Authors:
Julia Oh

All Authors:
Akintunde Emiola,Julia Oh

评论