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....
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ftunivtoronto:oai:localhost:1807/86862 2023-05-15T17:58:14+02:00 Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality Jiang, Yue Xiong, Xuejian Danska, Jayne Parkinson, John 2016-01-12 http://hdl.handle.net/1807/86862 https://doi.org/10.1186/s40168-015-0146-x en eng Microbiome. 2016 Jan 12;4(1):2 http://dx.doi.org/10.1186/s40168-015-0146-x http://hdl.handle.net/1807/86862 Jiang et al. Journal Article 2016 ftunivtoronto https://doi.org/10.1186/s40168-015-0146-x 2020-06-17T12:16:05Z 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 . Article in Journal/Newspaper permafrost University of Toronto: Research Repository T-Space Microbiome 4 1 |
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Open Polar |
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University of Toronto: Research Repository T-Space |
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ftunivtoronto |
language |
English |
description |
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 . |
format |
Article in Journal/Newspaper |
author |
Jiang, Yue Xiong, Xuejian Danska, Jayne Parkinson, John |
spellingShingle |
Jiang, Yue Xiong, Xuejian Danska, Jayne Parkinson, John Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality |
author_facet |
Jiang, Yue Xiong, Xuejian Danska, Jayne Parkinson, John |
author_sort |
Jiang, Yue |
title |
Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality |
title_short |
Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality |
title_full |
Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality |
title_fullStr |
Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality |
title_full_unstemmed |
Metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality |
title_sort |
metatranscriptomic analysis of diverse microbial communities reveals core metabolic pathways and microbiome-specific functionality |
publishDate |
2016 |
url |
http://hdl.handle.net/1807/86862 https://doi.org/10.1186/s40168-015-0146-x |
genre |
permafrost |
genre_facet |
permafrost |
op_relation |
Microbiome. 2016 Jan 12;4(1):2 http://dx.doi.org/10.1186/s40168-015-0146-x http://hdl.handle.net/1807/86862 |
op_rights |
Jiang et al. |
op_doi |
https://doi.org/10.1186/s40168-015-0146-x |
container_title |
Microbiome |
container_volume |
4 |
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1 |
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1766166797257539584 |