Prediction and quantification of bioactive microbiota metabolites in the mouse gut

Gautham V. Sridharan, Kyungoh Choi, Cory Klemashevich, Charmian Wu, Darshan Prabakaran, Long Bin Pan, Shelby Steinmeyer, Carrie Mueller, Mona Yousofshahi, Robert C. Alaniz, Kyongbum Lee () and Arul Jayaraman ()
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Gautham V. Sridharan: Tufts University
Kyungoh Choi: Texas A&M University
Cory Klemashevich: Texas A&M University
Charmian Wu: Tufts University
Darshan Prabakaran: Texas A&M University
Long Bin Pan: Tufts University
Shelby Steinmeyer: Texas A&M Health Science Center
Carrie Mueller: Texas A&M Health Science Center
Robert C. Alaniz: Texas A&M Health Science Center
Kyongbum Lee: Tufts University
Arul Jayaraman: Texas A&M University

Nature Communications, 2014, vol. 5, issue 1, 1-13

Abstract: Abstract 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.

Date: 2014
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DOI: 10.1038/ncomms6492

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