Metatranscriptome analysis of the human fecal microbiota reveals subject-specific expression profiles, with genes encoding proteins involved in carbohydrate metabolism being dominantly expressed
- PMID: 20562280
- PMCID: PMC2918960
- DOI: 10.1128/AEM.00502-10
Metatranscriptome analysis of the human fecal microbiota reveals subject-specific expression profiles, with genes encoding proteins involved in carbohydrate metabolism being dominantly expressed
Abstract
The human gastrointestinal (GI) tract provides home to a complex microbial community, collectively termed microbiota. Although major efforts have been made to describe the diversity and stability of the microbiota, functional studies have been largely restricted to intestinal isolates and include few community studies. The aim of this study was to explore the in situ gene expression of the fecal microbiota and to evaluate the RNA fingerprinting method cDNA-AFLP (cDNA amplified fragment length polymorphism) for this purpose. To this end, cDNA-AFLP analysis of enriched mRNA revealed that two healthy subjects showed highly divergent expression profiles with considerable fluctuations in time. Subsequent excision and sequence determination of bands from the mRNA-enriched profiles resulted in 122 identifiable sequences (transcripts and rRNAs). The classification of retrieved transcripts into functional clusters based on COG (cluster of orthologous genes) annotation showed that most assigned transcripts belonged to the metabolism cluster (26% of all sequences), underlining that even at the very end of the intestinal tract the microbiota is still very active. This study furthermore revealed that cDNA-AFLP is a useful tool to compare gene expression profiles in time in complex microbial communities.
Figures




Similar articles
-
A comprehensive metatranscriptome analysis pipeline and its validation using human small intestine microbiota datasets.BMC Genomics. 2013 Aug 2;14:530. doi: 10.1186/1471-2164-14-530. BMC Genomics. 2013. PMID: 23915218 Free PMC article.
-
Relating the metatranscriptome and metagenome of the human gut.Proc Natl Acad Sci U S A. 2014 Jun 3;111(22):E2329-38. doi: 10.1073/pnas.1319284111. Epub 2014 May 19. Proc Natl Acad Sci U S A. 2014. PMID: 24843156 Free PMC article.
-
High taxonomic level fingerprint of the human intestinal microbiota by ligase detection reaction--universal array approach.BMC Microbiol. 2010 Apr 19;10:116. doi: 10.1186/1471-2180-10-116. BMC Microbiol. 2010. PMID: 20398430 Free PMC article.
-
Large-scale Gene Ontology analysis of plant transcriptome-derived sequences retrieved by AFLP technology.BMC Genomics. 2008 Jul 24;9:347. doi: 10.1186/1471-2164-9-347. BMC Genomics. 2008. PMID: 18652646 Free PMC article.
-
Development of a fluorophore-ribosomal DNA restriction typing method for monitoring structural shifts of microbial communities.Arch Microbiol. 2011 May;193(5):341-50. doi: 10.1007/s00203-011-0679-8. Epub 2011 Jan 28. Arch Microbiol. 2011. PMID: 21274516
Cited by
-
Comparative meta-RNA-seq of the vaginal microbiota and differential expression by Lactobacillus iners in health and dysbiosis.Microbiome. 2013 Apr 12;1(1):12. doi: 10.1186/2049-2618-1-12. Microbiome. 2013. PMID: 24450540 Free PMC article.
-
Functional dynamics of bacterial species in the mouse gut microbiome revealed by metagenomic and metatranscriptomic analyses.PLoS One. 2020 Jan 24;15(1):e0227886. doi: 10.1371/journal.pone.0227886. eCollection 2020. PLoS One. 2020. PMID: 31978162 Free PMC article.
-
Comparison of assembly algorithms for improving rate of metatranscriptomic functional annotation.Microbiome. 2014 Oct 28;2:39. doi: 10.1186/2049-2618-2-39. eCollection 2014. Microbiome. 2014. PMID: 25411636 Free PMC article.
-
Chronic Rhinosinusitis and the Evolving Understanding of Microbial Ecology in Chronic Inflammatory Mucosal Disease.Clin Microbiol Rev. 2017 Jan;30(1):321-348. doi: 10.1128/CMR.00060-16. Clin Microbiol Rev. 2017. PMID: 27903594 Free PMC article. Review.
-
Metatranscriptomics analysis of cyanobacterial aggregates during cyanobacterial bloom period in Lake Taihu, China.Environ Sci Pollut Res Int. 2018 Feb;25(5):4811-4825. doi: 10.1007/s11356-017-0733-4. Epub 2017 Dec 3. Environ Sci Pollut Res Int. 2018. PMID: 29198031
References
-
- Altschul, S. F., W. Gish, W. Miller, E. W. Myers, and D. J. Lipman. 1990. Basic local alignment search tool. J. Mol. Biol. 215:403-410. - PubMed
-
- Asmann, Y. W., M. B. Wallace, and E. A. Thompson. 2008. Transcriptome profiling using next-generation sequencing. Gastroenterology 135:1466-1468. - PubMed
-
- Bachem, C. W., R. S. van der Hoeven, S. M. de Bruijn, D. Vreugdenhil, M. Zabeau, and R. G. Visser. 1996. Visualization of differential gene expression using a novel method of RNA fingerprinting based on AFLP: analysis of gene expression during potato tuber development. Plant J. 9:745-753. - PubMed
-
- Bachem, C. W. B., R. J. F. J. Oomen, and R. G. F. Visser. 1998. Transcript imaging with cDNA-AFLP: a step-by-step protocol. Plant Mol. Biol. Rep. 16:157-173.
Publication types
MeSH terms
Associated data
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
- Actions
LinkOut - more resources
Full Text Sources
Other Literature Sources
Medical
Molecular Biology Databases