title: 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.
authors.affiliation: Program in Molecular Structure and Function, The Hospital for Sick Children, Toronto, Canada.
authors.forename: Xuejian
authors.initials: X
authors.lastname: Xiong
authors.forename: Daniel N
authors.initials: DN
authors.lastname: Frank
authors.forename: Charles E
authors.initials: CE
authors.lastname: Robertson
authors.forename: Stacy S
authors.initials: SS
authors.lastname: Hung
authors.forename: Janet
authors.initials: J
authors.lastname: Markle
authors.forename: Angelo J
authors.initials: AJ
authors.lastname: Canty
authors.forename: Kathy D
authors.initials: KD
authors.lastname: McCoy
authors.forename: Andrew J
authors.initials: AJ
authors.lastname: Macpherson
authors.forename: Philippe
authors.initials: P
authors.lastname: Poussier
authors.forename: Jayne S
authors.initials: JS
authors.lastname: Danska
authors.forename: John
authors.initials: J
authors.lastname: Parkinson
mesh_terms: D000818:Animals; D001483:Base Sequence; D030541:Databases, Genetic; D004926:Escherichia coli / Q000235:genetics / Q000378:metabolism; D029968:Escherichia coli Proteins / Q000378:metabolism; D053263:Gene Regulatory Networks / Q000235:genetics; D005798:Genes, Bacterial / Q000235:genetics; D007413:Intestinal Mucosa / Q000378:metabolism*; D056186:Metagenomics / Q000379:methods*; D051379:Mice; D016688:Mice, Inbred NOD; D058977:Molecular Sequence Annotation; D005810:Multigene Family; D010455:Peptides / Q000378:metabolism; D010802:Phylogeny; D060066:Protein Interaction Maps; D012333:RNA, Messenger / Q000235:genetics / Q000378:metabolism; D012335:RNA, Ribosomal / Q000235:genetics; D054682:Ribosome Subunits, Small, Eukaryotic / Q000235:genetics; D017423:Sequence Analysis, RNA / Q000379:methods*; D059467:Transcriptome / Q000235:genetics*
chemical_list: D029968:Escherichia coli Proteins; D010455:Peptides; D012333:RNA, Messenger; D012335:RNA, Ribosomal