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      Mapping human microbiome drug metabolism by gut bacteria and their genes

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      Nature

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          Summary:

          Individuals vary widely in drug responses, which can be dangerous and expensive due to treatment delays and adverse effects. Growing evidence implicates the gut microbiome in this variability, however the molecular mechanisms remain largely unknown. We measured the ability of 76 diverse human gut bacteria to metabolize 271 oral drugs and found that many of these drugs are chemically modified by microbes. We combined high-throughput genetics with mass spectrometry to systematically identify drug-metabolizing microbial gene products. These microbiome-encoded enzymes can directly and significantly impact intestinal and systemic drug metabolism in mice and can explain drug-metabolizing activities of human gut bacteria and communities based on their genomic contents. These causal links between microbiota gene content and metabolic activities connect interpersonal microbiome variability to interpersonal differences in drug metabolism, which has implications for medical therapy and drug development across multiple disease indications.

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          Most cited references21

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          Identifying genetic determinants needed to establish a human gut symbiont in its habitat.

          The human gut microbiota is a metabolic organ whose cellular composition is determined by a dynamic process of selection and competition. To identify microbial genes required for establishment of human symbionts in the gut, we developed an approach (insertion sequencing, or INSeq) based on a mutagenic transposon that allows capture of adjacent chromosomal DNA to define its genomic location. We used massively parallel sequencing to monitor the relative abundance of tens of thousands of transposon mutants of a saccharolytic human gut bacterium, Bacteroides thetaiotaomicron, as they established themselves in wild-type and immunodeficient gnotobiotic mice, in the presence or absence of other human gut commensals. In vivo selection transforms this population, revealing functions necessary for survival in the gut: we show how this selection is influenced by community composition and competition for nutrients (vitamin B(12)). INSeq provides a broadly applicable platform to explore microbial adaptation to the gut and other ecosystems.
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            Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice.

            The proportion of the human gut bacterial community that is recalcitrant to culture remains poorly defined. In this report, we combine high-throughput anaerobic culturing techniques with gnotobiotic animal husbandry and metagenomics to show that the human fecal microbiota consists largely of taxa and predicted functions that are represented in its readily cultured members. When transplanted into gnotobiotic mice, complete and cultured communities exhibit similar colonization dynamics, biogeographical distribution, and responses to dietary perturbations. Moreover, gnotobiotic mice can be used to shape these personalized culture collections to enrich for taxa suited to specific diets. We also demonstrate that thousands of isolates from a single donor can be clonally archived and taxonomically mapped in multiwell format to create personalized microbiota collections. Retrieving components of a microbiota that have coexisted in single donors who have physiologic or disease phenotypes of interest and reuniting them in various combinations in gnotobiotic mice should facilitate preclinical studies designed to determine the degree to which tractable bacterial taxa are able to transmit donor traits or influence host biology.
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              Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism.

              We provide a demonstration in humans of the principle of pharmacometabonomics by showing a clear connection between an individual's metabolic phenotype, in the form of a predose urinary metabolite profile, and the metabolic fate of a standard dose of the widely used analgesic acetaminophen. Predose and postdose urinary metabolite profiles were determined by (1)H NMR spectroscopy. The predose spectra were statistically analyzed in relation to drug metabolite excretion to detect predose biomarkers of drug fate and a human-gut microbiome cometabolite predictor was identified. Thus, we found that individuals having high predose urinary levels of p-cresol sulfate had low postdose urinary ratios of acetaminophen sulfate to acetaminophen glucuronide. We conclude that, in individuals with high bacterially mediated p-cresol generation, competitive O-sulfonation of p-cresol reduces the effective systemic capacity to sulfonate acetaminophen. Given that acetaminophen is such a widely used and seemingly well-understood drug, this finding provides a clear demonstration of the immense potential and power of the pharmacometabonomic approach. However, we expect many other sulfonation reactions to be similarly affected by competition with p-cresol and our finding also has important implications for certain diseases as well as for the variable responses induced by many different drugs and xenobiotics. We propose that assessing the effects of microbiome activity should be an integral part of pharmaceutical development and of personalized health care. Furthermore, we envisage that gut bacterial populations might be deliberately manipulated to improve drug efficacy and to reduce adverse drug reactions.
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                Author and article information

                Journal
                0410462
                6011
                Nature
                Nature
                Nature
                0028-0836
                1476-4687
                6 June 2019
                03 June 2019
                June 2019
                03 December 2019
                : 570
                : 7762
                : 462-467
                Affiliations
                Department of Microbial Pathogenesis and Microbial Sciences Institute, Yale University School of Medicine, New Haven, CT 06536, USA
                Author notes
                Correspondence to A.L.G.: andrew.goodman@ 123456yale.edu

                Author Contributions: M.Z. and A.L.G. conceived and initiated the project; M.Z. performed the experiments; M.Z. and R.W. established the gain-of-function pipeline; M.Z. and M.Z.K. analyzed the data; M.Z.K. performed statistical analyses and prepared graphical illustrations; M.Z., M.Z.K. and A.L.G. wrote the manuscript.

                [*]

                These authors contributed equally to this work.

                [1]

                Present address: Department of Biology, Institute of Molecular Systems Biology, ETH Zurich, Switzerland

                Article
                NIHMS1530152
                10.1038/s41586-019-1291-3
                6597290
                31158845
                485b93ea-ad89-4113-a295-27604456839b

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