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A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets

BACKGROUND: Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretat...

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Autores principales: Leimena, Milkha M, Ramiro-Garcia, Javier, Davids, Mark, van den Bogert, Bartholomeus, Smidt, Hauke, Smid, Eddy J, Boekhorst, Jos, Zoetendal, Erwin G, Schaap, Peter J, Kleerebezem, Michiel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750648/
https://www.ncbi.nlm.nih.gov/pubmed/23915218
http://dx.doi.org/10.1186/1471-2164-14-530
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author Leimena, Milkha M
Ramiro-Garcia, Javier
Davids, Mark
van den Bogert, Bartholomeus
Smidt, Hauke
Smid, Eddy J
Boekhorst, Jos
Zoetendal, Erwin G
Schaap, Peter J
Kleerebezem, Michiel
author_facet Leimena, Milkha M
Ramiro-Garcia, Javier
Davids, Mark
van den Bogert, Bartholomeus
Smidt, Hauke
Smid, Eddy J
Boekhorst, Jos
Zoetendal, Erwin G
Schaap, Peter J
Kleerebezem, Michiel
author_sort Leimena, Milkha M
collection PubMed
description BACKGROUND: Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretation of which requires a reliable bioinformatic pipeline. In this study, we focus on the development of such a metatranscriptome pipeline, which we validate using Illumina RNA-seq datasets derived from the small intestine microbiota of two individuals with an ileostomy. RESULTS: The metatranscriptome pipeline developed here enabled effective removal of rRNA derived sequences, followed by confident assignment of the predicted function and taxonomic origin of the mRNA reads. Phylogenetic analysis of the small intestine metatranscriptome datasets revealed a strong similarity with the community composition profiles obtained from 16S rDNA and rRNA pyrosequencing, indicating considerable congruency between community composition (rDNA), and the taxonomic distribution of overall (rRNA) and specific (mRNA) activity among its microbial members. Reproducibility of the metatranscriptome sequencing approach was established by independent duplicate experiments. In addition, comparison of metatranscriptome analysis employing single- or paired-end sequencing methods indicated that the latter approach does not provide improved functional or phylogenetic insights. Metatranscriptome functional-mapping allowed the analysis of global, and genus specific activity of the microbiota, and illustrated the potential of these approaches to unravel syntrophic interactions in microbial ecosystems. CONCLUSIONS: A reliable pipeline for metatransciptome data analysis was developed and evaluated using RNA-seq datasets obtained for the human small intestine microbiota. The set-up of the pipeline is very generic and can be applied for (bacterial) metatranscriptome analysis in any chosen niche.
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spelling pubmed-37506482013-08-24 A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets Leimena, Milkha M Ramiro-Garcia, Javier Davids, Mark van den Bogert, Bartholomeus Smidt, Hauke Smid, Eddy J Boekhorst, Jos Zoetendal, Erwin G Schaap, Peter J Kleerebezem, Michiel BMC Genomics Research Article BACKGROUND: Next generation sequencing (NGS) technologies can be applied in complex microbial ecosystems for metatranscriptome analysis by employing direct cDNA sequencing, which is known as RNA sequencing (RNA-seq). RNA-seq generates large datasets of great complexity, the comprehensive interpretation of which requires a reliable bioinformatic pipeline. In this study, we focus on the development of such a metatranscriptome pipeline, which we validate using Illumina RNA-seq datasets derived from the small intestine microbiota of two individuals with an ileostomy. RESULTS: The metatranscriptome pipeline developed here enabled effective removal of rRNA derived sequences, followed by confident assignment of the predicted function and taxonomic origin of the mRNA reads. Phylogenetic analysis of the small intestine metatranscriptome datasets revealed a strong similarity with the community composition profiles obtained from 16S rDNA and rRNA pyrosequencing, indicating considerable congruency between community composition (rDNA), and the taxonomic distribution of overall (rRNA) and specific (mRNA) activity among its microbial members. Reproducibility of the metatranscriptome sequencing approach was established by independent duplicate experiments. In addition, comparison of metatranscriptome analysis employing single- or paired-end sequencing methods indicated that the latter approach does not provide improved functional or phylogenetic insights. Metatranscriptome functional-mapping allowed the analysis of global, and genus specific activity of the microbiota, and illustrated the potential of these approaches to unravel syntrophic interactions in microbial ecosystems. CONCLUSIONS: A reliable pipeline for metatransciptome data analysis was developed and evaluated using RNA-seq datasets obtained for the human small intestine microbiota. The set-up of the pipeline is very generic and can be applied for (bacterial) metatranscriptome analysis in any chosen niche. BioMed Central 2013-08-02 /pmc/articles/PMC3750648/ /pubmed/23915218 http://dx.doi.org/10.1186/1471-2164-14-530 Text en Copyright © 2013 Leimena et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Leimena, Milkha M
Ramiro-Garcia, Javier
Davids, Mark
van den Bogert, Bartholomeus
Smidt, Hauke
Smid, Eddy J
Boekhorst, Jos
Zoetendal, Erwin G
Schaap, Peter J
Kleerebezem, Michiel
A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets
title A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets
title_full A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets
title_fullStr A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets
title_full_unstemmed A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets
title_short A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets
title_sort comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3750648/
https://www.ncbi.nlm.nih.gov/pubmed/23915218
http://dx.doi.org/10.1186/1471-2164-14-530
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