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Individual drugs show variations in how successful or toxic they are, person to person. Now, by observing how varieties of genetically manipulated microbiota in the guts of mice contribute to the metabolization of drugs, researchers have revealed new insights into how these bacterial residents impact overall drug response and effectiveness. Their study provides a new framework by which to disentangle the complex interactions between host and microbiome metabolisms. The results could help enable the development of medications designed to improve treatment success by tailoring them to a patient’s gut microbiota.
The thriving microbial communities that inhabit the human gut forage and metabolize nearly everything they encounter, including orally administered drugs. As a result, the metabolism of drugs by the host body is influenced by the specific composition of an individual’s microbiota, which has been implicated in the wide variations of how successful – or toxic – drugs are among individuals. However, distinguishing and measuring the microbial contributions to drug metabolism has remained a challenge – particularly if the metabolic processes and products are chemically indistinguishable between the host and microbiome.
Michael Zimmerman and colleagues measured the levels of the drug brivudine (BRV) and its known metabolite, bromovinyluracil (BVU), over time and across different tissues within mice inoculated with a variety of gut communities – some complex, some gnotobiotic and some genetically modified. The authors identified a buildup of BVU (known to lead to deadly interactions with other drugs) in the livers of mice with complex biomes, illustrating the contribution of microbiota to drug toxicity. Using this data, Zimmerman et al. developed a pharmacokinetic model, which was able to computationally predict the contributions of both the host and microbiome in the metabolism of other anti-viral and anti-depressant drugs.
According to the results of the model, in some scenarios, nearly 70% of drug metabolism could be predicted from the activity of microbiota.
IMAGE SOURCE: Creative Commons