Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing.
Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing.
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DOI：
10.1371/journal.pone.0036009
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发表时间：
2012
期刊：
影响因子：
3.7
通讯作者：
Parkinson J
中科院分区：
文献类型：
--
作者：
Xiong X;Frank DN;Robertson CE;Hung SS;Markle J;Canty AJ;McCoy KD;Macpherson AJ;Poussier P;Danska JS;Parkinson J
随着高通量测序（HTS）的出现，新兴的宏基因组学科学正在改变我们对微生物群落与环境关系的理解。虽然宏基因组学旨在通过评估哪些基因被活跃表达来对样本中存在的基因进行编目，但元转录组学可以提供对社区相互关系的机械理解。为了实现这些目标，需要解决从样品制备到序列处理、统计分析和功能注释的几个挑战。在这里，我们使用了一个近交系非肥胖糖尿病（NOD）小鼠模型，其中无菌动物与八种肠道细菌的定义混合物定殖，探索RNA提取的方法，并开发一个管道的生成和分析的元转录组数据。应用Illumina HTS平台，我们对使用多种RNA提取方案制备的12个NOD盲肠样品进行测序。由于缺乏一套完整的参考基因组，因此需要基于肽的搜索策略。高达16%的序列读数可以与已知的细菌基因相匹配。系统发育分析的映射ORF揭示了核糖体RNA的分布一致，大多数从拟杆菌属或梭菌属物种。为了将这些HTS数据置于系统背景下，我们将相应的大肠杆菌同系物的相对丰度映射到代谢和蛋白质-蛋白质相互作用网络上。这些图谱识别出了具有在数据集中得到充分代表的组分的细菌过程。总之，这项研究强调了利用HTS平台进行元转录组学的经济潜力。
With the advent of high through-put sequencing (HTS), the emerging science of metagenomics is transforming our understanding of the relationships of microbial communities with their environments. While metagenomics aims to catalogue the genes present in a sample through assessing which genes are actively expressed, metatranscriptomics can provide a mechanistic understanding of community inter-relationships. To achieve these goals, several challenges need to be addressed from sample preparation to sequence processing, statistical analysis and functional annotation. Here we use an inbred non-obese diabetic (NOD) mouse model in which germ-free animals were colonized with a defined mixture of eight commensal bacteria, to explore methods of RNA extraction and to develop a pipeline for the generation and analysis of metatranscriptomic data. Applying the Illumina HTS platform, we sequenced 12 NOD cecal samples prepared using multiple RNA-extraction protocols. The absence of a complete set of reference genomes necessitated a peptide-based search strategy. Up to 16% of sequence reads could be matched to a known bacterial gene. Phylogenetic analysis of the mapped ORFs revealed a distribution consistent with ribosomal RNA, the majority from Bacteroides or Clostridium species. To place these HTS data within a systems context, we mapped the relative abundance of corresponding Escherichia coli homologs onto metabolic and protein-protein interaction networks. These maps identified bacterial processes with components that were well-represented in the datasets. In summary this study highlights the potential of exploiting the economy of HTS platforms for metatranscriptomics.
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影响因子：
3.7
作者：
Gilbert JA;Field D;Swift P;Thomas S;Cummings D;Temperton B;Weynberg K;Huse S;Hughes M;Joint I;Somerfield PJ;Mühling M
通讯作者：
Mühling M
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56.9
作者：
Gill, Steven R.;Pop, Mihai;Nelson, Karen E.
通讯作者：
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影响因子：
14.9
作者：
Bairoch, A;Apweiler, R
通讯作者：
Apweiler, R
影响因子：
11
作者：
Baumgart, Martin;Dogan, Belgin;Simpson, Kenneth W.
通讯作者：
Simpson, Kenneth W.
影响因子：
9.8
作者：
Hu P;Janga SC;Babu M;Díaz-Mejía JJ;Butland G;Yang W;Pogoutse O;Guo X;Phanse S;Wong P;Chandran S;Christopoulos C;Nazarians-Armavil A;Nasseri NK;Musso G;Ali M;Nazemof N;Eroukova V;Golshani A;Paccanaro A;Greenblatt JF;Moreno-Hagelsieb G;Emili A
通讯作者：
Emili A