Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing

Xuejian Xiong, Daniel N. Frank, Charles E. Robertson, Stacy S. Hung, Janet Markle, Angelo J. Canty, Kathy D. McCoy, Andrew J. Macpherson, Philippe Poussier, Jayne S. Danska, John Parkinson

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Article numbere36009
JournalPLoS One
Volume7
Issue number4
DOIs
StatePublished - Apr 27 2012
Externally publishedYes

Fingerprint

RNA Sequence Analysis
Metagenomics
Bacterial Physiological Phenomena
sequence analysis
Genes
RNA
Protein Interaction Maps
Bacterial Genes
Inbred NOD Mouse
Bacteroides
Ribosomal RNA
Clostridium
mice
germ-free animals
Open Reading Frames
genes
protein-protein interactions
Genome
Escherichia coli
Bacteria

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)

Cite this

Xiong, X., Frank, D. N., Robertson, C. E., Hung, S. S., Markle, J., Canty, A. J., ... Parkinson, J. (2012). Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing. PLoS One, 7(4), [e36009]. https://doi.org/10.1371/journal.pone.0036009

Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing. / Xiong, Xuejian; Frank, Daniel N.; Robertson, Charles E.; Hung, Stacy S.; Markle, Janet; Canty, Angelo J.; McCoy, Kathy D.; Macpherson, Andrew J.; Poussier, Philippe; Danska, Jayne S.; Parkinson, John.

In: PLoS One, Vol. 7, No. 4, e36009, 27.04.2012.

Research output: Contribution to journalArticle

Xiong, X, Frank, DN, Robertson, CE, Hung, SS, Markle, J, Canty, AJ, McCoy, KD, Macpherson, AJ, Poussier, P, Danska, JS & Parkinson, J 2012, 'Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing', PLoS One, vol. 7, no. 4, e36009. https://doi.org/10.1371/journal.pone.0036009
Xiong, Xuejian ; Frank, Daniel N. ; Robertson, Charles E. ; Hung, Stacy S. ; Markle, Janet ; Canty, Angelo J. ; McCoy, Kathy D. ; Macpherson, Andrew J. ; Poussier, Philippe ; Danska, Jayne S. ; Parkinson, John. / Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing. In: PLoS One. 2012 ; Vol. 7, No. 4.
@article{9cd1c0356f52425d88dc5346b55737af,
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.",
author = "Xuejian Xiong and Frank, {Daniel N.} and Robertson, {Charles E.} and Hung, {Stacy S.} and Janet Markle and Canty, {Angelo J.} and McCoy, {Kathy D.} and Macpherson, {Andrew J.} and Philippe Poussier and Danska, {Jayne S.} and John Parkinson",
year = "2012",
month = "4",
day = "27",
doi = "10.1371/journal.pone.0036009",
language = "English (US)",
volume = "7",
journal = "PLoS One",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "4",

}

TY - JOUR

T1 - Generation and analysis of a mouse intestinal metatranscriptome through Illumina based RNA-sequencing

AU - Xiong, Xuejian

AU - Frank, Daniel N.

AU - Robertson, Charles E.

AU - Hung, Stacy S.

AU - Markle, Janet

AU - Canty, Angelo J.

AU - McCoy, Kathy D.

AU - Macpherson, Andrew J.

AU - Poussier, Philippe

AU - Danska, Jayne S.

AU - Parkinson, John

PY - 2012/4/27

Y1 - 2012/4/27

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=84860477454&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84860477454&partnerID=8YFLogxK

U2 - 10.1371/journal.pone.0036009

DO - 10.1371/journal.pone.0036009

M3 - Article

VL - 7

JO - PLoS One

JF - PLoS One

SN - 1932-6203

IS - 4

M1 - e36009

ER -