Metatranscriptome analysis of the human fecal microbiota reveals subject-specific expression profiles, with genes encoding proteins involved in carbohydrate metabolism being dominantly expressed

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 fe...

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Veröffentlicht in:Applied and environmental microbiology Jg. 76; H. 16; S. 5533
Hauptverfasser: Booijink, Carien C G M, Boekhorst, Jos, Zoetendal, Erwin G, Smidt, Hauke, Kleerebezem, Michiel, de Vos, Willem M
Format: Journal Article
Sprache:Englisch
Veröffentlicht: United States 01.08.2010
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ISSN:1098-5336, 1098-5336
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Zusammenfassung: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.
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ISSN:1098-5336
1098-5336
DOI:10.1128/AEM.00502-10