| Literature DB >> 28642381 |
Nitzan Koppel1, Vayu Maini Rekdal1, Emily P Balskus2,3.
Abstract
The human gut microbiota makes key contributions to the metabolism of ingested compounds (xenobiotics), transforming hundreds of dietary components, industrial chemicals, and pharmaceuticals into metabolites with altered activities,Entities:
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Year: 2017 PMID: 28642381 PMCID: PMC5534341 DOI: 10.1126/science.aag2770
Source DB: PubMed Journal: Science ISSN: 0036-8075 Impact factor: 47.728
Fig. 1Identifying gut microbial genes that predict cardiac drug metabolism. (A) E. lenta reductive metabolism leads to cardiac drug inactivation. (B) A combination of culture-based studies, sequencing, and bioinformatics helped to identify microbial genes associated with digoxin metabolism in humans.
Fig. 2Uncovering gut microbial enzymes that convert dietary choline to disease-associated metabolites. (A) Choline is metabolized by a gut microbial-human co-metabolic pathway into the disease-associated metabolites trimethylamine (TMA) and trimethylamine N-oxide (TMAO). (B) A chemically guided, rational genome-mining effort enabled the identification and characterization of enzymes involved in gut microbial anaerobic choline metabolism.
Fig. 3Preventing drug reactivation and toxicity by inhibiting gut microbial enzymes. (A) Microbial cleavage of the glucuronidated drug conjugate of the cancer chemotherapeutic SN-38 leads to drug reactivation and toxicity within the gut. UDP, uridine diphosphate. (B) High-throughput screening identified specific inhibitors of bacterial β-glucuronidases. These compounds alleviated the GI toxicity associated with irinotecan metabolism. Et, ethyl.
Fig. 4Potential implications of understanding gut microbial xenobiotic metabolism. (A) Interfacing clinical studies and hypothesis-driven research in model systems is essential for elucidating the biological consequences of gut microbial xenobiotic metabolism. Incorporating a mechanistic understanding of microbial transformations, along with knowledge of host genetics and metabolism, could (B) inform personalized nutrition, (C) improve toxicological risk assessment, and (D) enable personalized medicine.