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, B53% 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.
BackgroundContamination of the environment with bioactive chemicals has emerged as a potential public health risk. These substances that may cause distress or disease in humans can be found in air, water and food supplies. An open question is whether these chemicals transform into potentially more active or toxic derivatives via xenobiotic metabolizing enzymes expressed in the body. We present a new prediction tool, which we call PROXIMAL (Prediction of Xenobiotic Metabolism) for identifying possible transformation products of xenobiotic chemicals in the liver. Using reaction data from DrugBank and KEGG, PROXIMAL builds look-up tables that catalog the sites and types of structural modifications performed by Phase I and Phase II enzymes. Given a compound of interest, PROXIMAL searches for substructures that match the sites cataloged in the look-up tables, applies the corresponding modifications to generate a panel of possible transformation products, and ranks the products based on the activity and abundance of the enzymes involved.ResultsPROXIMAL generates transformations that are specific for the chemical of interest by analyzing the chemical’s substructures. We evaluate the accuracy of PROXIMAL’s predictions through case studies on two environmental chemicals with suspected endocrine disrupting activity, bisphenol A (BPA) and 4-chlorobiphenyl (PCB3). Comparisons with published reports confirm 5 out of 7 and 17 out of 26 of the predicted derivatives for BPA and PCB3, respectively. We also compare biotransformation predictions generated by PROXIMAL with those generated by METEOR and Metaprint2D-react, two other prediction tools.ConclusionsPROXIMAL can predict transformations of chemicals that contain substructures recognizable by human liver enzymes. It also has the ability to rank the predicted metabolites based on the activity and abundance of enzymes involved in xenobiotic transformation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12918-015-0241-4) contains supplementary material, which is available to authorized users.
The design, development, and engineering of drugs provide chemical engineers with many opportunities and challenges in the pharmaceutical industry. In an effort to engage the surrounding communities, New York City public and private high school students were introduced to the field of pharmaceutical engineering over the course of six weeks. Through the use of lectures, teamwork activities, and laboratory experiments, students learned about the fundamentals of oral solid dosage forms, drug dissolution, and experimental design. Examples of experiments performed include building their own "in-house" drug dissolution devices, studying the effect of impeller geometry and velocity on dissolution rates, and obtaining drug dissolution profiles for various oral solid dosage forms containing Ibuprofen using UV-Vis spectroscopy. Students were also trained in communication skills, such as writing a technical report and giving an oral presentation.
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