title: Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality.
abstract: BACKGROUND
  Metatranscriptomics is emerging as a powerful technology for the functional characterization of complex microbial communities (microbiomes). Use of unbiased RNA-sequencing can reveal both the taxonomic composition and active biochemical functions of a complex microbial community. However, the lack of established reference genomes, computational tools and pipelines make analysis and interpretation of these datasets challenging. Systematic studies that compare data across microbiomes are needed to demonstrate the ability of such pipelines to deliver biologically meaningful insights on microbiome function.
  
  
  RESULTS
  Here, we apply a standardized analytical pipeline to perform a comparative analysis of metatranscriptomic data from diverse microbial communities derived from mouse large intestine, cow rumen, kimchi culture, deep-sea thermal vent and permafrost. Sequence similarity searches allowed annotation of 19 to 76% of putative messenger RNA (mRNA) reads, with the highest frequency in the kimchi dataset due to its relatively low complexity and availability of closely related reference genomes. Metatranscriptomic datasets exhibited distinct taxonomic and functional signatures. From a metabolic perspective, we identified a common core of enzymes involved in amino acid, energy and nucleotide metabolism and also identified microbiome-specific pathways such as phosphonate metabolism (deep sea) and glycan degradation pathways (cow rumen). Integrating taxonomic and functional annotations within a novel visualization framework revealed the contribution of different taxa to metabolic pathways, allowing the identification of taxa that contribute unique functions.
  
  
  CONCLUSIONS
  The application of a single, standard pipeline confirms that the rich taxonomic and functional diversity observed across microbiomes is not simply an artefact of different analysis pipelines but instead reflects distinct environmental influences. At the same time, our findings show how microbiome complexity and availability of reference genomes can impact comprehensive annotation of metatranscriptomes. Consequently, beyond the application of standardized pipelines, additional caution must be taken when interpreting their output and performing downstream, microbiome-specific, analyses. The pipeline used in these analyses along with a tutorial has been made freely available for download from our project website: http://www.compsysbio.org/microbiome .
authors.affiliation: Program in Molecular Structure and Function, The Hospital for Sick Children, Peter Gilgan Center for Research and Learning, 686 Bay Street, Toronto, ON, M5G 0A4, Canada. jiangxxuan@gmail.com.
authors.forename: Yue
authors.initials: Y
authors.lastname: Jiang
authors.affiliation: Program in Molecular Structure and Function, The Hospital for Sick Children, Peter Gilgan Center for Research and Learning, 686 Bay Street, Toronto, ON, M5G 0A4, Canada. xiongxuejian@hotmail.com.
authors.forename: Xuejian
authors.initials: X
authors.lastname: Xiong
authors.affiliation: Department of Immunology, University of Toronto, Toronto, ON, Canada. jayne.danska@sickkids.ca.|Program in Genetics and Genomic Biology, The Hospital for Sick Children, Toronto, ON, Canada. jayne.danska@sickkids.ca.|Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada. jayne.danska@sickkids.ca.
authors.forename: Jayne
authors.initials: J
authors.lastname: Danska
authors.affiliation: Program in Molecular Structure and Function, The Hospital for Sick Children, Peter Gilgan Center for Research and Learning, 686 Bay Street, Toronto, ON, M5G 0A4, Canada. jparkin@sickkids.ca.|Departments of Biochemistry, Computer Science and Molecular Genetics, University of Toronto, Toronto, ON, Canada. jparkin@sickkids.ca.|Centre for the Analysis of Genome Evolution, University of Toronto, Toronto, ON, Canada. jparkin@sickkids.ca.
authors.forename: John
authors.initials: J
authors.lastname: Parkinson
mesh_terms: D000818:Animals; D001937:Brassica / Q000382:microbiology; D002417:Cattle; D005285:Fermentation; D063990:Gene Ontology; D060086:Hydrothermal Vents / Q000382:microbiology; D007420:Intestine, Large / Q000382:microbiology; D053858:Metabolic Networks and Pathways / Q000235:genetics*; D054892:Metagenome; D051379:Mice; D064307:Microbiota / Q000235:genetics*; D058977:Molecular Sequence Annotation; D065946:Permafrost / Q000382:microbiology; D010802:Phylogeny; D012329:RNA, Bacterial / Q000235:genetics*; D012333:RNA, Messenger / Q000235:genetics*; D031224:Raphanus / Q000382:microbiology; D012417:Rumen / Q000382:microbiology; D017423:Sequence Analysis, RNA
chemical_list: D012329:RNA, Bacterial; D012333:RNA, Messenger