Generation and Analysis of a Mouse Intestinal Metatranscriptome through Illumina Based RNA-Sequencing

Abstract

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.

Rhizosphere microbiome assemblage is affected by plant development

“…Plant development influences the functional capacity of the rhizomicrobiome Metatranscriptomics analyses of mRNA have only recently been used as a means to study microbial communities at a functional level in distinct environments such as the human gut (Gosalbes et al, 2011), the mouse gut (Xiong et al, 2012) and 7 160 167 198 1 199 366 Phenolics 31 139 170 222 57 279 449 Sugars 51 0 51 0 82 82 133 Sugar Alcohols 0 47 47 85 6 91 138 The values indicate the number of significant (Po0.05) correlations.…”

IDBA-MTP: A Hybrid Metatranscriptomic Assembler Based on Protein Information

“…We compared the performances of Oases [26], Trinity [10], IDBA-UD [21], IDBA-MT [15] and IDBA-MTP on a real dataset from mouse gut [32] and two simulated datasets generated from known bacteria gene sequences obtained from genBank [1]. Oases and Trinity were designed for assembling transcriptomic data, IDBA-UD for assembling metagenomic data, and IDBA-MT for assembling metatranscriptomic data.…”

“…Existing work tries to reconstruct mRNAs by aligning metatranscriptomic reads to known genomes or gene DNA sequences. However, this approach has had only limited success [32] as the genomes of most microbes are still unknown [4] and the microbe gene sequences mutate frequently.…”

“…Second, to consider amino acid, the information contained in a single read becomes much less (3 nucleotides converted to 1 amino acid). Since one read only corresponds to about 25 amino acids (aa), it is difficult to have a confident alignment [32]. Another approach is to align contigs, instead of reads, to proteins.…”

“…Xiong et al [32] isolated mRNAs from the lumen of the cecum and colon of 4 mice at 12 weeks old, colonized with an Altered Schaedler flora (ASF) containing eight known species without reference genomes. A total of 3.3 million paired-end reads were generated using Illumina sequencing technology.…”