Prediction and quantification of bioactive microbiota metabolites in the mouse gut

Metabolites produced by the intestinal microbiota are potentially important physiological modulators. Here we present a metabolomics strategy that models microbiota metabolism as a reaction network and utilizes pathway analysis to facilitate identification and characterization of microbiota metaboli...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Nature communications 2014-11, Vol.5 (1), p.5492-5492, Article 5492
Hauptverfasser: Sridharan, Gautham V., Choi, Kyungoh, Klemashevich, Cory, Wu, Charmian, Prabakaran, Darshan, Pan, Long Bin, Steinmeyer, Shelby, Mueller, Carrie, Yousofshahi, Mona, Alaniz, Robert C., Lee, Kyongbum, Jayaraman, Arul
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Metabolites produced by the intestinal microbiota are potentially important physiological modulators. Here we present a metabolomics strategy that models microbiota metabolism as a reaction network and utilizes pathway analysis to facilitate identification and characterization of microbiota metabolites. Of the 2,409 reactions in the model, ~53% do not occur in the host, and thus represent functions dependent on the microbiota. The largest group of such reactions involves amino-acid metabolism. Focusing on aromatic amino acids, we predict metabolic products that can be derived from these sources, while discriminating between microbiota- and host-dependent derivatives. We confirm the presence of 26 out of 49 predicted metabolites, and quantify their levels in the caecum of control and germ-free mice using two independent mass spectrometry methods. We further investigate the bioactivity of the confirmed metabolites, and identify two microbiota-generated metabolites (5-hydroxy-L-tryptophan and salicylate) as activators of the aryl hydrocarbon receptor. Metabolites produced by the gut microbiota can potentially affect our physiology. Here, the authors present a metabolomics strategy that models microbiota metabolism as a reaction network and uses pathway analysis to facilitate identification and characterization of microbial metabolites.
ISSN:2041-1723
2041-1723
DOI:10.1038/ncomms6492