12-19 利用高通量tRNA测序和调控分析描绘微生物组群特征

Microbiome characterization by high-throughput transfer RNA sequencing and modification analysis

题目：利用高通量tRNA测序和调控分析描绘微生物组群特征

作者：

Michael H. Schwartz, Haipeng Wang, Jessica N. Pan, [...], Tao Pan & A. Murat Eren

通讯作者单位：

A. Murat Eren:

Committee on Microbiology, University of Chicago, Chicago, IL, 60637, USA
Department of Medicine, University of Chicago, Chicago, IL, 60637, USA
Marine Biological Laboratory, Woods Hole, MA, 02543, USA

Tao Pan:

Department of Biochemistry and Molecular Biology, University of Chicago, Chicago, IL, 60637, USA
Committee on Microbiology, University of Chicago, Chicago, IL, 60637, USA

发表期刊及时间：

Nature Communications volume 9, Article number: 5353 (2018)

Published 17 December 2018

摘要：

Advances in high-throughput sequencing have facilitated remarkable insights into the diversity and functioning of naturally occurring microbes; however, current sequencing strategies are insufficient to reveal physiological states of microbial communities associated with protein translation dynamics. Transfer RNAs (tRNAs) are core components of protein synthesis machinery, present in all living cells, and are phylogenetically tractable, which make them ideal targets to gain physiological insights into environmental microbes. Here we report a direct sequencing approach, tRNA-seq, and a software suite, tRNA-seq-tools, to recover sequences, abundance profiles, and post-transcriptional modifications of microbial tRNA transcripts. Our analysis of cecal samples using tRNA-seq distinguishes high-fat- and low-fat- fed mice in a comparable fashion to 16S ribosomal RNA gene amplicons, and reveals taxon- and diet-dependent variations in tRNA modifications. Our results provide taxon-specific in situ insights into the dynamics of tRNA gene expression and post-transcriptional mod- ifications within complex environmental microbiomes.

高通量测序的发展促进了人们对天然存在的微生物的多样性和功能的卓越的认识；但是，现有的测序策略不足以揭示与蛋白质翻译动力学相关的微生物组群的生理状态。转运RNA（tRNA）是蛋白质合成工具的核心成分，存在于所有活细胞当中，在系统发育上很容易追溯，这些特征让它们成为了获得环境微生物生理学见解的理想靶点。这里，我们报道了一个直接的测序方法tRNA-seq，以及配套的软件tRNA-seq-tools，以复原微生物tRNA转录物的序列，丰度谱和转录后修饰。我们使用tRNA-seq分析盲肠样品，利用比较16S核糖体RNA基因扩增子的方式区分高脂肪和低脂肪喂养的小鼠，并揭示tRNA修饰中的分类和饮食依赖性变异。我们的研究结果提供了对复杂环境微生物组中tRNA基因表达和转录后修饰动态的分类特异性原位洞察。

图表选析

Fig 3. Microbiome tRNA-seq workflow and taxonomy analysis. 图3. 微生物组tRNA-seq工作流程和分类学分析

a Workflow of tRNA sequencing of gut microbiome samples fed with a high-fat (HF) or low- fat (LF) diet and de novo tRNA assignment. Conserved tRNA residues that were searched for in this work are shown in red.
b Dendrograms compare relationships between HF and LF samples that were inferred based on community profiles of tRNA transcripts, or 16S rRNA gene amplicons.
c Class-level taxonomy for averaged HF and LF samples based on tRNA-seq (top) and 16S rRNA gene amplicons (bottom). All bacterial classes at >1% level are shown in distinct colors, all other bacterial classes are grouped together and shown in purple.
d tRNAGly taxonomy for anticodons GCC, UCC, and CCC.
e tRNAGlu taxonomy for anticodons UUC and CUC. Among the other category for GCC/UCC/CCC and UUC, no class has an abundance of ≥1%; for CUC, other classes with an abundance of ≥1% include Alphaproteobacteria, Gemmatimonadetes, and Ignavibacteria. tRNAs decoding these two amino acids are the most abundant in our tRNA-seq results

a 用高脂肪饮食组（HF）或低脂肪饮食组（LF）的肠道微生物组样品的tRNA测序以及tRNA重新匹配的工作流程。此工作中寻找到的保守tRNA残基被标注为红色。
b 系统树图，比较HF组和LF租两个样品的关系，这些关系基于tRNA转录物或16S rRNA基因扩增子的群组特征推断得到。
c 基于tRNA-seq（上图）和16S rRNA基因扩增子（下图）的平均HF和LF样品的类级分类。所有> 1％水平的细菌类别以不同的颜色显示，所有其他细菌类别组合在一起并以紫色显示。
d 甘氨酸tRNA反密码子GCC, UCC, 和 CCC 的分类.
e 谷氨酸tRNA反密码子UUC和CUC的分类。在GCC / UCC / CCC和UUC的其他类别中，没有一个类别的丰度≥1％；对于CUC，其他丰度≥1％的类别包括甲型变形菌（Alphaproteobacteria），芽单胞菌（Gemmatimonadetes）和Ignavibacteria（无中文名）。在我们的tRNA-seq结果中这两种氨基酸的tRNA是最丰富的。