Gut Microbiome and Drug Metabolism

Main Article Content

E.N. Ilina
E.M. Mayorova
A.I. Manolov
A.A. Korenkova
V.V. Bahmetjev
K.S. Gorbunov


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.

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How to Cite
Ilina, E., Mayorova, E., Manolov, A., Korenkova, A., Bahmetjev, V., & Gorbunov, K. (2021). Gut Microbiome and Drug Metabolism. Biomedical Chemistry: Research and Methods, 4(1), e00146.


  1. Nebert, D.W., Zhang, G., Vesell, E.S. (2008). From human genetics and genomics to pharmacogenetics and pharmacogenomics: past lessons, future directions. Drug Metabolism Reviews, 40(2), 187–224. DOI
  2. Sender, R., Fuchs, S., & Milo, R. (2016). Revised Estimates for the Number of Human and Bacteria Cells in the Body. PLoS Biology, 14(8), e1002533. DOI
  3. Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., Yamada, T., Mende, D. R., Li, J., Xu, J., Li, S., Li, D., Cao, J., Wang, B., Liang, H., Zheng, H., Xie, Y., Tap, J., Lepage, P., Bertalan, M., Batto, J.M., Hansen, T., Le Paslie,r D., Linneberg, A., Nielsen, H.B., Pelletier, E., Renault, P., Sicheritz-Ponten, T., Turner, K., Zhu, H., Yu, C., Li, S., Jian, M., Zhou, Y., Li, Y., Zhang, X., Li S., Qin, N., Yang, H., Wang, J., Brunak, S., Doré J., Guarner, F., Kristiansen, K., Pedersen, O., Parkhill, J., Weissenbach, J., MetaHIT Consortium, Bork, P., Ehrlich, S.D., Wang, J. (2010). A human gut microbial gene catalogue established by metagenomic sequencing. Nature, 464(7285), 59–65. DOI
  4. Moya, A., & Ferrer, M. (2016). Functional Redundancy-Induced Stability of Gut Microbiota Subjected to Disturbance. Trends in Microbiology, 24(5), 402–413. DOI
  5. Spanogiannopoulos, P., Bess, E. N., Carmody, R. N., & Turnbaugh, P. J. (2016). The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism. Nature Reviews. Microbiology, 14(5), 273–287. DOI
  6. Haiser, H. J., & Turnbaugh, P. J. (2013). Developing a metagenomic view of xenobiotic metabolism. Pharmacological Research, 69(1), 21–31. DOI
  7. Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R., & Goodman, A. L. (2019). Separating host and microbiome contributions to drug pharmacokinetics and toxicity. Science (New York, N.Y.), 363(6427), eaat9931. DOI
  8. Singh, K. S., Sharma, R., Reddy, P., Vonteddu, P., Good, M., Sundarrajan, A., Choi, H., Muthumani, K., Kossenkov, A., Goldman, A. R., Tang, H. Y., Totrov, M., Cassel, J., Murphy, M. E., Somasundaram, R., Herlyn, M., Salvino, J. M., & Dotiwala, F. (2021). IspH inhibitors kill Gram-negative bacteria and mobilize immune clearance. Nature, 589(7843), 597–602. DOI
  9. Zimmermann, M., Zimmermann-Kogadeeva, M., Wegmann, R., Goodman, A.L. (2019). Mapping human microbiome drug metabolism by gut bacteria and their genes. Nature. 570(7762), 462-467. DOI
  10. Choi, M. S., Yu, J. S., Yoo, H. H., & Kim, D. H. (2018). The role of gut microbiota in the pharmacokinetics of antihypertensive drugs. Pharmacological Research, 130, 164–171. DOI
  11. Guo, Y., Lee, H., & Jeong, H. (2020). Gut microbiota in reductive drug metabolism. Progress in Molecular Biology and Translational Science, 171, 61–93. DOI
  12. Wang, Y., Zhang, C., Hou, S., Wu, X., Liu, J., & Wan, X. (2020). Analyses of Potential Driver and Passenger Bacteria in Human Colorectal Cancer. Cancer Management and Research, 12, 11553–11561. DOI
  13. Shi, H., Shi, Q., Grodner, B., Lenz, J. S., Zipfel, W. R., Brito, I. L., & De Vlaminck, I. (2020). Highly multiplexed spatial mapping of microbial communities. Nature, 588(7839), 676–681. DOI
  14. Straussman, R., Morikawa, T., Shee, K., Barzily-Rokni, M., Qian, Z. R., Du, J., Davis, A., Mongare, M. M., Gould, J., Frederick, D. T., Cooper, Z. A., Chapman, P. B., Solit, D. B., Ribas, A., Lo, R. S., Flaherty, K. T., Ogino, S., Wargo, J. A., & Golub, T. R. (2012). Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion. Nature, 487(7408), 500–504. DOI
  15. Geller, L. T., Barzily-Rokni, M., Danino, T., Jonas, O. H., Shental, N., Nejman, D., Gavert, N., Zwang, Y., Cooper, Z. A., Shee, K., Thaiss, C. A., Reuben, A., Livny, J., Avraham, R., Frederick, D. T., Ligorio, M., Chatman, K., Johnston, S. E., Mosher, C. M., Brandis, A., Fuks, G., Gurbatri, C., Gopalakrishnan, V., Kim, M., Hurd, M.W., Katz, M., Fleming, J., Maitra, A., Smith, D.A., Skalak, M., Bu, J., Michaud, M., Trauger, S.A., Barshack, I., Golan, T., Sandbank, J., Flaherty, K.T., Mandinova, A., Garrett, W.S., Thayer, S.P., Ferrone, C.R., Huttenhower, C., Bhatia, S.N., Gevers, D., Wargo, J.A., Golub, T.R., Straussman, R. (2017). Potential role of intratumor bacteria in mediating tumor resistance to the chemotherapeutic drug gemcitabine. Science, 357(6356), 1156–1160. DOI
  16. Mima, K., Nishihara, R., Qian, Z. R., Cao, Y., Sukawa, Y., Nowak, J. A., Yang, J., Dou, R., Masugi, Y., Song, M., Kostic, A. D., Giannakis, M., Bullman, S., Milner, D. A., Baba, H., Giovannucci, E. L., Garraway, L. A., Freeman, G. J., Dranoff, G., Garrett, W. S., Huttenhower, C., Meyerson, M., Meyerhardt, J.A., Chan, A.T., Fuchs, C.S., Ogino, S. (2016). Fusobacterium nucleatum in colorectal carcinoma tissue and patient prognosis. Gut, 65(12), 1973–1980. DOI
  17. Yu, T., Guo, F., Yu, Y., Sun, T., Ma, D., Han, J., Qian, Y., Kryczek, I., Sun, D., Nagarsheth, N., Chen, Y., Chen, H., Hong, J., Zou, W., Fang, J. Y. (2017). Fusobacterium nucleatum Promotes Chemoresistance to Colorectal Cancer by Modulating Autophagy. Cell, 170(3), 411-413. DOI
  18. Björkholm, B., Bok, C. M., Lundin, A., Rafter, J., Hibberd, M. L., & Pettersson, S. (2009). Intestinal microbiota regulate xenobiotic metabolism in the liver. PloS One, 4(9), e6958. DOI
  19. Clayton, T. A., Baker, D., Lindon, J. C., Everett, J. R., & Nicholson, J. K. (2009). Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism. Proceedings of the National Academy of Sciences of the United States of America, 106(34), 14728–14733. DOI
  20. Stein, A., Voigt, W., & Jordan, K. (2010). Chemotherapy-induced diarrhea: pathophysiology, frequency and guideline-based management. Therapeutic Advances in Medical Oncology, 2(1), 51–63. DOI
  21. Higuchi, K., Umegaki, E., Watanabe, T., Yoda, Y., Morita, E., Murano, M., Tokioka, S., & Arakawa, T. (2009). Present status and strategy of NSAIDs-induced small bowel injury. Journal of Gastroenterology, 44(9), 879–888. DOI
  22. Hooper, L. V., Wong, M. H., Thelin, A., Hansson, L., Falk, P. G., & Gordon, J. I. (2001). Molecular analysis of commensal host-microbial relationships in the intestine. Science, 291(5505), 881–884. DOI
  23. Claus, S. P., Ellero, S. L., Berger, B., Krause, L., Bruttin, A., Molina, J., Paris, A., Want, E. J., de Waziers, I., Cloarec, O., Richards, S. E., Wang, Y., Dumas, M. E., Ross, A., Rezzi, S., Kochhar, S., Van Bladeren, P., Lindon, J. C., Holmes, E., & Nicholson, J. K. (2011). Colonization-induced host-gut microbial metabolic interaction. mBio, 2(2), e00271-10. DOI
  24. Wikoff, W. R., Anfora, A. T., Liu, J., Schultz, P. G., Lesley, S. A., Peters, E. C., & Siuzdak, G. (2009). Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proceedings of the National Academy of Sciences of the United States of America, 106(10), 3698–3703. DOI
  25. Claus, S. P., Tsang, T. M., Wang, Y., Cloarec, O., Skordi, E., Martin, F. P., Rezzi, S., Ross, A., Kochhar, S., Holmes, E., & Nicholson, J. K. (2008). Systemic multicompartmental effects of the gut microbiome on mouse metabolic phenotypes. Molecular systems biology, 4, 219. DOI
  26. Pond, S. M., & Tozer, T. N. (1984). First-pass elimination. Basic concepts and clinical consequences. Clinical Pharmacokinetics, 9(1), 1–25. DOI
  27. Deloménie, C., Fouix, S., Longuemaux, S., Brahimi, N., Bizet, C., Picard, B., Denamur, E., & Dupret, J. M. (2001). Identification and functional characterization of arylamine N-acetyltransferases in eubacteria: evidence for highly selective acetylation of 5-aminosalicylic acid. Journal of Bacteriology, 183(11), 3417–3427. DOI
  28. Sousa, T., Yadav, V., Zann, V., Borde, A., Abrahamsson, B., & Basit, A. W. (2014). On the colonic bacterial metabolism of azo-bonded prodrugsof 5-aminosalicylic acid. Journal of Pharmaceutical Sciences, 103(10), 3171–3175. DOI
  29. Olekhnovich, E. I., Manolov, A. I., Pavlenko, A. V., Konanov, D. N., Fedorov, D. E., Tikhonova, P. O., Glushchenko, O. E., Ilina, E. N. (2020). Intestinal microbiom modulates the response to antitumor immunotherapy. Biomeditsinskaya Khimiya, 66(1), 54-63. DOI
  30. Hamid, O., Robert, C., Daud, A., Hodi, F. S., Hwu, W. J., Kefford, R., Wolchok, J. D., Hersey, P., Joseph, R. W., Weber, J. S., Dronca, R., Gangadhar, T. C., Patnaik, A., Zarour, H., Joshua, A. M., Gergich, K., Elassaiss-Schaap, J., Algazi, A., Mateus, C., Boasberg, P., … Ribas, A. (2013). Safety and tumor responses with lambrolizumab (anti-PD-1) in melanoma. The New England Journal of Medicine, 369(2), 134–144. DOI
  31. Fedorov, D. E., Olekhnovich, E. I., Pavlenko, A. V., Klimina, K. M., Pokataev, I. A., Manolov, A. I., Konanov, D. N., Veselovsky, V. A., Ilina, E. N. (2020). Intestinal microbiome as a predictor of the anti-PD-1 therapy success: metagenomic data analysis. Biomeditsinskaya Khimiya, 66(6), 502-507. DOI
  32. Klaassen, C. D., & Cui, J. Y. (2015). Review: Mechanisms of How the Intestinal Microbiota Alters the Effects of Drugs and Bile Acids. Drug Metabolism and Disposition, 43(10), 1505–1521. DOI
  33. Maurice, C. F., Haiser, H. J., & Turnbaugh, P. J. (2013). Xenobiotics shape the physiology and gene expression of the active human gut microbiome. Cell, 152(1-2), 39–50. DOI
  34. Tsiaoussis, J., Antoniou, M. N., Koliarakis, I., Mesnage, R., Vardavas, C. I., Izotov, B. N., Psaroulaki, A., & Tsatsakis, A. (2019). Effects of single and combined toxic exposures on the gut microbiome: Current knowledge and future directions. Toxicology Letters, 312, 72–97. DOI
  35. David, L. A., Maurice, C. F., Carmody, R. N., Gootenberg, D. B., Button, J. E., Wolfe, B. E., Ling, A. V., Devlin, A. S., Varma, Y., Fischbach, M. A., Biddinger, S. B., Dutton, R. J., & Turnbaugh, P. J. (2014). Diet rapidly and reproducibly alters the human gut microbiome. Nature, 505(7484), 559–563. DOI
  36. Frommknecht H. (1988). Der Arzt--Partner der Privaten Krankenversicherung [The physician--the partner of private health insurance]. Versicherungsmedizin, 40(2), 33–34.
  37. Usenbaev A. (1971). Blood indices and their changes following blood giving by donors in different geographic localities. Sovetskoe zdravookhranenie Kirgizii, 1, 3–7.
  38. Palacios-González, B., Ramírez-Salazar, E. G., Rivera-Paredez, B., Quiterio, M., Flores, Y. N., Macias-Kauffer, L., Moran-Ramos, S., Denova-Gutiérrez, E., Ibarra-González, I., Vela-Amieva, M., Canizales-Quinteros, S., Salmerón, J., Velázquez-Cruz, R. (2020). A multi-omic analysis for low bone mineral density in postmenopausal women suggests a relationship between diet, metabolites, and microbiota. Microorganisms, 8(11), 1630. DOI
  39. Haiser, H. J., Gootenberg, D. B., Chatman, K., Sirasani, G., Balskus, E. P., & Turnbaugh, P. J. (2013). Predicting and manipulating cardiac drug inactivation by the human gut bacterium Eggerthella lenta. Science, 341(6143), 295–298. DOI
  40. Guthrie, L., Wolfson, S., & Kelly, L. (2019). The human gut chemical landscape predicts microbe-mediated biotransformation of foods and drugs. eLife, 8, e42866. DOI
  41. Integrative HMP (iHMP) Research Network Consortium (2014). The Integrative Human Microbiome Project: dynamic analysis of microbiome-host omics profiles during periods of human health and disease. Cell Host and Microbe, 16(3), 276–289. DOI
  42. Zhang, J., Wu, J., Li, H., Chen, Q., & Lin, J. M. (2015). An in vitro liver model on microfluidic device for analysis of capecitabine metabolite using mass spectrometer as detector. Biosensors & Bioelectronics, 68, 322–328. DOI
  43. Li, Z., Su, W., Zhu, Y., Tao, T., Li, D., Peng, X., & Qin, J. (2017). Drug absorption related nephrotoxicity assessment on an intestine-kidney chip. Biomicrofluidics, 11(3), 034114. DOI
  44. Sung J. H. (2020). A body-on-a-chip (BOC) system for studying gut-liver interaction. Methods in Cell Biology, 158, 1–10. DOI
  45. Picollet-D'hahan, N., Zuchowska, A., Lemeunier, I., & Le Gac, S. (2021). Multiorgan-on-a-Chip: A Systemic Approach To Model and Decipher Inter-Organ Communication. Trends in Biotechnology. Advance online publication. DOI
  46. An, F., Qu, Y., Luo, Y., Fang, N., Liu, Y., Gao, Z., Zhao, W., & Lin, B. (2016). A Laminated Microfluidic Device for Comprehensive Preclinical Testing in the Drug ADME Process. Scientific Reports, 6, 25022. DOI
  47. Esch, M. B., Mahler, G. J., Stokol, T., & Shuler, M. L. (2014). Body-on-a-chip simulation with gastrointestinal tract and liver tissues suggests that ingested nanoparticles have the potential to cause liver injury. Lab on a Chip, 14(16), 3081–3092. DOI
  48. Sung, J. H., Esch, M. B., Prot, J. M., Long, C. J., Smith, A., Hickman, J. J., & Shuler, M. L. (2013). Microfabricated mammalian organ systems and their integration into models of whole animals and humans. Lab on a Chip, 13(7), 1201–1212. DOI
  49. Ekkers, D. M., Branco Dos Santos, F., Mallon, C. A., Bruggeman, F., & van Doorn, G. S. (2020). The omnistat: A flexible continuous-culture system for prolonged experimental evolution. Methods in Ecology and Evolution, 11(8), 932–942. DOI
  50. Liu, Y., El Masoudi, A., Pronk, J. T., & van Gulik, W. M. (2019). Quantitative Physiology of Non-Energy-Limited Retentostat Cultures of Saccharomyces cerevisiae at Near-Zero Specific Growth Rates. Applied and Environmental Microbiology, 85(20), e01161-19. DOI
  51. Holt, L. J., Hallatschek, O., & Delarue, M. (2018). Mechano-chemostats to study the effects of compressive stress on yeast. Methods in Cell Biology, 147, 215–231. DOI
  52. Ekkers, D. M., Branco Dos Santos, F., Mallon, C. A., Bruggeman, F., & van Doorn, G. S. (2020). The omnistat: A flexible continuous-culture system for prolonged experimental evolution. Methods in Ecology and Evolution, 11(8), 932–942. DOI
  53. Spence, J. R., Mayhew, C. N., Rankin, S. A., Kuhar, M. F., Vallance, J. E., Tolle, K., Hoskins, E. E., Kalinichenko, V. V., Wells, S. I., Zorn, A. M., Shroyer, N. F., & Wells, J. M. (2011). Directed differentiation of human pluripotent stem cells into intestinal tissue in vitro. Nature, 470(7332), 105–109. DOI
  54. Hill, D. R., Huang, S., Nagy, M. S., Yadagiri, V. K., Fields, C., Mukherjee, D., Bons, B., Dedhia, P. H., Chin, A. M., Tsai, Y. H., Thodla, S., Schmidt, T. M., Walk, S., Young, V. B., & Spence, J. R. (2017). Bacterial colonization stimulates a complex physiological response in the immature human intestinal epithelium. eLife, 6, e29132. DOI
  55. Kolawole, A. O., & Wobus, C. E. (2020). Gastrointestinal organoid technology advances studies of enteric virus biology. PLoS pathogens, 16(1), e1008212. DOI
  56. Barrila, J., Crabbé, A., Yang, J., Franco, K., Nydam, S. D., Forsyth, R. J., Davis, R. R., Gangaraju, S., Ott, C. M., Coyne, C. B., Bissell, M. J., & Nickerson, C. A. (2018). Modeling host-pathogen interactions in the context of the microenvironment: three-dimensional cell culture comes of age. Infection and Immunity, 86(11), e00282-18. DOI
  57. Pusch, J., Votteler, M., Göhler, S., Engl, J., Hampel, M., Walles, H., & Schenke-Layland, K. (2011). The physiological performance of a three-dimensional model that mimics the microenvironment of the small intestine. Biomaterials, 32(30), 7469–7478. DOI
  58. Ingber D. E. (2016). Reverse Engineering Human Pathophysiology with Organs-on-Chips. Cell, 164(6), 1105–1109. DOI
  59. Imura, Y., Asano, Y., Sato, K., & Yoshimura, E. (2009). A microfluidic system to evaluate intestinal absorption. Analytical Sciences: the International Journal of the Japan Society for Analytical Chemistry, 25(12), 1403–1407. DOI
  60. Shah, P., Fritz, J. V., Glaab, E., Desai, M. S., Greenhalgh, K., Frachet, A., Niegowska, M., Estes, M., Jäger, C., Seguin-Devaux, C., Zenhausern, F., & Wilmes, P. (2016). A microfluidics-based in vitro model of the gastrointestinal human-microbe interface. Nature communications, 7, 11535. DOI
  61. Eain, M. M. G., Baginska, J., Greenhalgh, K., Fritz, J. V., Zenhausern, F., & Wilmes, P. (2017). Engineering solutions for representative models of the gastrointestinal human-microbe interface. Engineering, 3(1), 60-65. DOI
  62. Jalili-Firoozinezhad, S., Gazzaniga, F. S., Calamari, E. L., Camacho, D. M., Fadel, C. W., Bein, A., Swenor, B., Nestor, B., Cronce, M. J., Tovaglieri, A., Levy, O., Gregory, K. E., Breault, D. T., Cabral, J., Kasper, D. L., Novak, R., & Ingber, D. E. (2019). A complex human gut microbiome cultured in an anaerobic intestine-on-a-chip. Nature Biomedical Engineering, 3(7), 520–531. DOI