Gut Microbiome and Drug Metabolism - Ilina, E.N.; Mayorova, E.M.; Manolov, A.I.; Korenkova, A.A.; Bahmetjev, V.V.; Gorbunov, K.S. (Biomedical Chemistry: Research and Methods, 2021)
The human physiology textbooks traditionally consider the intestine as a metabolically active organ, with its activity primarily associated with the production of numerous digestive enzymes. The development of molecular analysis technologies has significantly detailized this picture, primarily by decoding the metabolic potential of the intestinal microbiota. Data from numerous metagenomic studies indicate that the number of eukaryotic and bacterial cells in the human body is comparable - about 3.0×1013, while the number of genes in the intestinal metagenome is one hundred times greater than in the human genome. Obviously, the gut microbiota exhibits both direct and indirect effects on the metabolism of drugs and xenobiotics, that can affect their effectiveness and toxicity. Orally administrated xenobiotics have been found to be metabolized by intestinal microbial enzymes before being absorbed from the gastrointestinal tract into the blood flow. The metabolic reactions performed by the gut microbiota greatly differ from the metabolic reactions of the liver, providing modification of drugs by acetylation, deacetylation, decarboxylation, dehydroxylation, demethylation, dehalogenation, etc. Despite the metabolism of xenobiotics by microbial enzymes of the intestine is rather known, information about the specific microflora mediating each metabolic reaction is still limited, mainly by the lack of an adequate model of the intestinal microbial community to allow the accumulation of experimental data for the creation of computational models. Currently, studies of drug metabolism use microfluidic chips, reproducing functions of various organs and tissues, such as the liver, kidney, lungs and intestine, as in vitro models in the form of 2D and 3D cell cultures. Supplementation of such systems with the microbial community will allow to get as close as possible to in vitro modeling of complicated biological processes in the interests of pharmacological research and the accumulation of data for constructing computational models.