Prediction, Identification, and Quantification of Microbiota Derived Metabolites in Murine Gut. - Pan, Long Bin. (Tufts Archival Research Center, 2005)
Recent studies have shown that the gastrointestinal (GI) tract microbiota plays an important role in the modulation of human health and disease. Disruptions in microbiota composition, dysbiosis, directly correlate with inflammatory bowel diseases, chronic diseases, and cardiovascular diseases (Nyangale et al., 2012). Beneficial processes of the microbiota include providing immune functions, maintaining epithelial barrier integrity, extracting nutrient and vitamin from host diets, and carrying out metabolic biotransformation reactions that are not readily available to the host organism (Bien et al., 2013). Substrates that escape digestion in the upper GI tract are utilized by the GI microbiota to produce a complex variety of metabolites. Current processes of identifying the spectrum of metabolites in the GI tract include isolation and characterization of individual bacterial species and untargeted metabolomics approaches. However, these methodologies do not account for the community-wide interactions of bacterial species and the host organism. These approaches also do not differentiate between metabolites produced by the GI microbiota and those by the host. In this study, a targeted metabolomics approach was utilized to predict, identify and quantify a set of metabolites that are nonnative to the host organism. A novel in silico approach was used to predict a set of potential anti-inflammatory metabolites derived from amino acid sources. Analyses with tandem mass spectrometry and high performance liquid chromatography were performed to quantify the levels of predicted metabolites in order to validate the accuracy of the in silico probabilistic algorithm. AhR activation experiments were used to verify the anti-inflammatory properties of metabolites because studies have shown that AhR, a ligand activated transcription factor, plays an important role in intestinal immune functions (Bjeldanes et al., 1991). Once anti-inflammatory metabolites have been determined and analyzed, they can be used for drug discovery and therapeutics.