Separating host and microbiome contributions to drug pharmacokinetics and toxicity
Anything humans swallow is exposed to the foraging and transforming activities of the gut microbiota. This applies to therapeutic drugs as well as food components and can be a major source of interpersonal variation in drug efficacy and toxicity. Zimmermann et al. found that individual drug response...
Saved in:
Published in | Science (American Association for the Advancement of Science) Vol. 363; no. 6427; p. 600 |
---|---|
Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
American Association for the Advancement of Science
08.02.2019
The American Association for the Advancement of Science |
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Anything humans swallow is exposed to the foraging and transforming activities of the gut microbiota. This applies to therapeutic drugs as well as food components and can be a major source of interpersonal variation in drug efficacy and toxicity. Zimmermann
et al.
found that individual drug responses depend on the genetics of an individual's microbiota. They explored the metabolism of nucleoside drugs (which are used as antivirals and antidepressants) in mice inoculated with a variety of mutant microbiota. They then modeled the pharmacokinetics in different body compartments and identified the host and microbe contributions. In some individuals, up to 70% of drug transformation can be ascribed to microbial metabolism.
Science
, this issue p.
eaat9931
Genetic manipulation of drug metabolism in human gut commensal bacteria resolves host and microbiome contributions.
The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to drug metabolism is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. We combined gut commensal genetics with gnotobiotics to measure brivudine drug metabolism across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model that quantitatively predicts microbiome contributions to systemic drug and metabolite exposure, as a function of bioavailability, host and microbial drug-metabolizing activity, drug and metabolite absorption, and intestinal transit kinetics. Clonazepam studies illustrate how this approach disentangles microbiome contributions to metabolism of drugs subject to multiple metabolic routes and transformations. |
---|---|
AbstractList | The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to drug metabolism is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. We combined gut commensal genetics with gnotobiotics to measure brivudine drug metabolism across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model that quantitatively predicts microbiome contributions to systemic drug and metabolite exposure, as a function of bioavailability, host and microbial drug-metabolizing activity, drug and metabolite absorption, and intestinal transit kinetics. Clonazepam studies illustrate how this approach disentangles microbiome contributions to metabolism of drugs subject to multiple metabolic routes and transformations.The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to drug metabolism is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. We combined gut commensal genetics with gnotobiotics to measure brivudine drug metabolism across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model that quantitatively predicts microbiome contributions to systemic drug and metabolite exposure, as a function of bioavailability, host and microbial drug-metabolizing activity, drug and metabolite absorption, and intestinal transit kinetics. Clonazepam studies illustrate how this approach disentangles microbiome contributions to metabolism of drugs subject to multiple metabolic routes and transformations. Off-target drug metabolismAnything humans swallow is exposed to the foraging and transforming activities of the gut microbiota. This applies to therapeutic drugs as well as food components and can be a major source of interpersonal variation in drug efficacy and toxicity. Zimmermann et al. found that individual drug responses depend on the genetics of an individual's microbiota. They explored the metabolism of nucleoside drugs (which are used as antivirals and antidepressants) in mice inoculated with a variety of mutant microbiota. They then modeled the pharmacokinetics in different body compartments and identified the host and microbe contributions. In some individuals, up to 70% of drug transformation can be ascribed to microbial metabolism.Science, this issue p. eaat9931INTRODUCTIONThe gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to drug metabolism in vivo is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. A quantitative understanding of the physiological, chemical, and microbial factors that determine microbiome contributions to drug metabolism could help explain interpersonal variability in drug response and provide opportunities for personalized medical treatments.RATIONALETo experimentally dissect microbiome and host drug metabolism, we combined gut commensal genetics with gnotobiotics to measure metabolism of the nucleoside analog brivudine (BRV) across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model to quantitatively predict microbiome contributions to systemic drug and metabolite exposure. Model simulations evaluate the impact of oral bioavailability, host and microbial drug-metabolizing activity, metabolite absorption, and intestinal transit on microbiome contributions to drug metabolism. To test the general applicability of this approach, we performed additional studies with the benzodiazepine clonazepam to quantitatively untangle microbiome contributions to metabolism of a drug subject to multiple metabolic routes and transformations.RESULTSWe demonstrate BRV conversion to hepatotoxic bromovinyluracil (BVU) by both mammalian and microbial enzymes and reduced systemic BVU exposure in germ-free mice, suggesting a microbiome contribution to serum BVU. Drug conversion assays with axenic cultures and an arrayed transposon library identified BRV-metabolizing gut bacteria and responsible gene products. This enabled us to establish mouse models that are isogenic except for a single bacterial gene responsible for microbial BRV metabolism. Administration of oral BRV and quantification of drug and drug metabolite kinetics in different body compartments provided the data to develop a host-microbiome pharmacokinetic model. This model accurately predicts serum BVU exposure and quantifies host and microbiome contributions to its pharmacokinetics. Model simulations revealed how drug, host, and microbial parameters affect host-microbiome drug metabolism.To test whether this approach applies to other microbiome-metabolized drugs, we quantified microbiome and host contributions to the metabolism of sorivudine, which is structurally related to BRV but is metabolized to BVU at different rates by both host and microbiome. We also quantified microbiome and host contributions to serum clonazepam metabolites produced through oxidation, nitroreduction, glucuronidation, and enterohepatic cycling.CONCLUSIONThis study provides an experimental and computational strategy to untangle host and microbial contributions to drug metabolism. Quantitative understanding of the interplay between host and microbiome-encoded metabolic activities will clarify how nutritional, environmental, genetic, and galenic factors affect drug metabolism and could enable tailored intervention strategies to improve drug responses. This approach could also be adapted to other xenobiotics, food components, and endogenous metabolites.The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to drug metabolism is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. We combined gut commensal genetics with gnotobiotics to measure brivudine drug metabolism across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model that quantitatively predicts microbiome contributions to systemic drug and metabolite exposure, as a function of bioavailability, host and microbial drug-metabolizing activity, drug and metabolite absorption, and intestinal transit kinetics. Clonazepam studies illustrate how this approach disentangles microbiome contributions to metabolism of drugs subject to multiple metabolic routes and transformations. Anything humans swallow is exposed to the foraging and transforming activities of the gut microbiota. This applies to therapeutic drugs as well as food components and can be a major source of interpersonal variation in drug efficacy and toxicity. Zimmermann et al. found that individual drug responses depend on the genetics of an individual's microbiota. They explored the metabolism of nucleoside drugs (which are used as antivirals and antidepressants) in mice inoculated with a variety of mutant microbiota. They then modeled the pharmacokinetics in different body compartments and identified the host and microbe contributions. In some individuals, up to 70% of drug transformation can be ascribed to microbial metabolism. Science , this issue p. eaat9931 Genetic manipulation of drug metabolism in human gut commensal bacteria resolves host and microbiome contributions. The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to drug metabolism is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. We combined gut commensal genetics with gnotobiotics to measure brivudine drug metabolism across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model that quantitatively predicts microbiome contributions to systemic drug and metabolite exposure, as a function of bioavailability, host and microbial drug-metabolizing activity, drug and metabolite absorption, and intestinal transit kinetics. Clonazepam studies illustrate how this approach disentangles microbiome contributions to metabolism of drugs subject to multiple metabolic routes and transformations. The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to drug metabolism is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. We combined gut commensal genetics with gnotobiotics to measure brivudine drug metabolism across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model that quantitatively predicts microbiome contributions to systemic drug and metabolite exposure, as a function of bioavailability, host and microbial drug-metabolizing activity, drug and metabolite absorption, and intestinal transit kinetics. Clonazepam studies illustrate how this approach disentangles microbiome contributions to metabolism of drugs subject to multiple metabolic routes and transformations. Genetic manipulation of drug metabolism in human gut commensal bacteria resolves host and microbiome contributions to a shared metabolic process. The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However, quantifying microbial contributions to drug metabolism is challenging, particularly in cases where host and microbiome perform the same metabolic transformation. We combined gut commensal genetics with gnotobiotics to measure brivudine drug metabolism across tissues in mice that vary in a single microbiome-encoded enzyme. Informed by these measurements, we built a pharmacokinetic model that quantitatively predicts microbiome contributions to systemic drug and metabolite exposure, as a function of bioavailability, host and microbial drug-metabolizing activity, drug and metabolite absorption, and intestinal transit kinetics. Clonazepam studies illustrate how this approach disentangles microbiome contributions to metabolism of drugs subject to multiple metabolic routes and transformations. |
Author | Zimmermann-Kogadeeva, Maria Goodman, Andrew L. Wegmann, Rebekka Zimmermann, Michael |
Author_xml | – sequence: 1 givenname: Michael surname: Zimmermann fullname: Zimmermann, Michael – sequence: 2 givenname: Maria surname: Zimmermann-Kogadeeva fullname: Zimmermann-Kogadeeva, Maria – sequence: 3 givenname: Rebekka surname: Wegmann fullname: Wegmann, Rebekka – sequence: 4 givenname: Andrew L. surname: Goodman fullname: Goodman, Andrew L. |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30733391$$D View this record in MEDLINE/PubMed |
BookMark | eNp1kc1r3DAQxUVJaTbbnntqMfTSixPJY1vWpRBCvyBQ6MdZjOXxrra2tJXk0vz3Vbqb0AZ6EmJ-7_HmzRk7cd4RY88FPxeiai-iseQMnSMmpUA8YivBVVOqisMJW3EObdlx2Zyysxh3nOeZgifsFLgEACVW7PMX2mPAZN2m2PqYCnRDMVsTfG_9TIXxLgXbL8l6F4vkiyEsm2K_xTCj8d-to2RN_KNK_pc1Nt08ZY9HnCI9O75r9u3d269XH8rrT-8_Xl1el6bhKpWmqqtaoGzrSvaVBKSxFgOIrjbYEIdRDaNAyj-pSBqogXeGtz30AgWRgjV7c_DdL_1Mg6GcFCe9D3bGcKM9Wv3vxNmt3vifum0ARG5ozV4fDYL_sVBMerbR0DShI79EXYkOcjoFVUZfPUB3fgkur5cpKbNZV8tMvfw70X2Uu7oz0ByA3G-MgUadC8PbbnNAO2nB9e1Z9fGs-njWrLt4oLuz_r_ixUGxi8mHe7xqm64TLYff6EuztQ |
CitedBy_id | crossref_primary_10_1080_19490976_2024_2305716 crossref_primary_10_1002_fsn3_70023 crossref_primary_10_3390_toxics9110308 crossref_primary_10_4269_ajtmh_20_0333 crossref_primary_10_3389_fmicb_2024_1429116 crossref_primary_10_1017_S0031182021000834 crossref_primary_10_3390_pharmaceutics13122001 crossref_primary_10_1038_s41579_020_0438_4 crossref_primary_10_1080_17425255_2024_2365254 crossref_primary_10_1016_j_tox_2021_152908 crossref_primary_10_1080_10408398_2022_2115456 crossref_primary_10_1016_j_toxlet_2024_04_013 crossref_primary_10_1080_19490976_2021_1872323 crossref_primary_10_1080_03602532_2023_2186313 crossref_primary_10_3389_fmicb_2021_752393 crossref_primary_10_1016_j_ejphar_2022_175209 crossref_primary_10_1128_MMBR_00072_19 crossref_primary_10_1016_j_jhazmat_2024_136152 crossref_primary_10_3389_fmicb_2023_1016872 crossref_primary_10_1016_j_ddmod_2019_08_004 crossref_primary_10_2139_ssrn_3354892 crossref_primary_10_1128_mmbr_00170_22 crossref_primary_10_1136_gutjnl_2022_327209 crossref_primary_10_1016_j_exger_2020_111095 crossref_primary_10_1186_s13213_023_01744_5 crossref_primary_10_1016_j_ijpsycho_2023_05_350 crossref_primary_10_1080_03602532_2020_1718691 crossref_primary_10_1016_j_jcmgh_2021_09_004 crossref_primary_10_1002_ame2_12364 crossref_primary_10_1371_journal_ppat_1008370 crossref_primary_10_1016_j_jfma_2022_09_010 crossref_primary_10_3389_fphar_2021_760280 crossref_primary_10_1016_j_mib_2022_102195 crossref_primary_10_1016_j_jpha_2021_10_003 crossref_primary_10_1080_17512433_2019_1670058 crossref_primary_10_1038_s41467_023_43279_y crossref_primary_10_1038_s41573_019_0053_0 crossref_primary_10_1016_j_nantod_2025_102665 crossref_primary_10_1111_1751_7915_13970 crossref_primary_10_1038_s41575_020_00397_y crossref_primary_10_3389_fchem_2022_907886 crossref_primary_10_3390_microorganisms12061070 crossref_primary_10_1080_17512433_2020_1759414 crossref_primary_10_1136_gutjnl_2019_320204 crossref_primary_10_1128_IAI_00012_20 crossref_primary_10_59400_jts_v2i2_1252 crossref_primary_10_1186_s12866_023_02801_4 crossref_primary_10_3389_fphar_2023_1047863 crossref_primary_10_1016_j_addr_2023_115051 crossref_primary_10_1080_10286020_2023_2251123 crossref_primary_10_1093_nar_gkaa755 crossref_primary_10_1038_s41684_021_00777_0 crossref_primary_10_3389_fendo_2019_00842 crossref_primary_10_1097_JS9_0000000000002147 crossref_primary_10_7554_eLife_82401 crossref_primary_10_2174_1389200223666220128141038 crossref_primary_10_1007_s40005_022_00600_z crossref_primary_10_1038_s41564_023_01581_x crossref_primary_10_15252_msb_202311525 crossref_primary_10_1016_j_nbd_2019_104576 crossref_primary_10_1186_s40168_020_00806_z crossref_primary_10_1002_jcph_1482 crossref_primary_10_1111_cts_13416 crossref_primary_10_1038_s41587_022_01628_0 crossref_primary_10_1007_s00280_019_03833_2 crossref_primary_10_1021_acs_chemrestox_9b00333 crossref_primary_10_1016_j_apsb_2019_10_001 crossref_primary_10_2139_ssrn_4200273 crossref_primary_10_1016_j_drudis_2020_12_009 crossref_primary_10_3390_molecules25030606 crossref_primary_10_1016_j_phrs_2019_104603 crossref_primary_10_1002_eji_202249866 crossref_primary_10_1360_SSV_2023_0179 crossref_primary_10_3390_cancers13040766 crossref_primary_10_3390_nu11092208 crossref_primary_10_1016_j_jare_2023_07_002 crossref_primary_10_1016_j_mib_2023_102333 crossref_primary_10_3389_fphar_2023_1333986 crossref_primary_10_3389_fmed_2022_972518 crossref_primary_10_1021_acs_biochem_1c00656 crossref_primary_10_1016_j_ijpharm_2024_124663 crossref_primary_10_1016_j_cotox_2023_100406 crossref_primary_10_3389_fmicb_2022_846915 crossref_primary_10_1016_j_cmet_2019_07_005 crossref_primary_10_1177_15357597221123907 crossref_primary_10_3389_fphar_2022_879170 crossref_primary_10_1038_s41576_022_00529_x crossref_primary_10_1002_pbc_28207 crossref_primary_10_1038_s41576_020_0244_x crossref_primary_10_1002_cpt_1510 crossref_primary_10_1161_HYPERTENSIONAHA_121_18711 crossref_primary_10_3389_fimmu_2021_742449 crossref_primary_10_3390_ph17081020 crossref_primary_10_1126_science_add5787 crossref_primary_10_1016_j_celrep_2020_107722 crossref_primary_10_59400_jts_v2i1_1252 crossref_primary_10_1080_19490976_2024_2356278 crossref_primary_10_1016_j_talanta_2021_122919 crossref_primary_10_1016_j_addr_2021_114076 crossref_primary_10_3390_biomedicines10040832 crossref_primary_10_20517_mrr_2023_24 crossref_primary_10_3389_fcell_2019_00362 crossref_primary_10_1038_s44324_024_00028_z crossref_primary_10_1021_acs_est_9b07854 crossref_primary_10_3390_microorganisms8101514 crossref_primary_10_1016_j_chom_2019_06_011 crossref_primary_10_2745_dds_35_309 crossref_primary_10_1016_j_ijpharm_2020_119379 crossref_primary_10_1177_1756284820974914 crossref_primary_10_1016_j_ijpharm_2020_119372 crossref_primary_10_1016_j_coph_2019_04_007 crossref_primary_10_3390_cancers14153599 crossref_primary_10_1002_adtp_202300449 crossref_primary_10_1126_science_aau6323 crossref_primary_10_1021_acs_chemrestox_0c00522 crossref_primary_10_4049_jimmunol_2100528 crossref_primary_10_1186_s40168_024_01768_2 crossref_primary_10_1016_j_bbrc_2023_09_064 crossref_primary_10_1080_19490976_2024_2374596 crossref_primary_10_3389_fmicb_2020_583525 crossref_primary_10_1002_mnfr_202200106 crossref_primary_10_1007_s40262_021_01032_y crossref_primary_10_1016_j_tem_2024_04_021 crossref_primary_10_1080_19490976_2019_1667724 crossref_primary_10_1038_s41398_024_02850_x crossref_primary_10_1016_j_lfs_2023_122357 crossref_primary_10_1126_science_ado8548 crossref_primary_10_1002_stem_3051 crossref_primary_10_1016_j_tem_2024_08_005 crossref_primary_10_1038_s41586_024_07754_w crossref_primary_10_1002_wnan_1892 crossref_primary_10_1007_s12275_022_1526_0 crossref_primary_10_1080_19490976_2024_2387400 crossref_primary_10_2131_jts_48_333 crossref_primary_10_1016_j_braindev_2024_09_002 crossref_primary_10_1021_jacs_1c10998 crossref_primary_10_1016_j_jpba_2019_113067 crossref_primary_10_1038_s41467_023_39264_0 crossref_primary_10_1136_pn_2024_004400 crossref_primary_10_1016_j_ntm_2023_100020 crossref_primary_10_1016_j_mmm_2022_01_004 crossref_primary_10_1080_03602532_2022_2097253 crossref_primary_10_3389_fphar_2021_663325 crossref_primary_10_1016_j_ejps_2021_105869 crossref_primary_10_1146_annurev_biochem_080320_115307 crossref_primary_10_1093_nar_gkaa924 crossref_primary_10_1016_j_scitotenv_2020_141867 crossref_primary_10_1038_s41586_019_1291_3 crossref_primary_10_1124_dmd_123_001605 crossref_primary_10_1016_j_biotechadv_2021_107797 crossref_primary_10_1128_mBio_02496_21 crossref_primary_10_3390_nu14245278 crossref_primary_10_1007_s12275_020_0066_8 crossref_primary_10_1186_s13073_022_01092_0 crossref_primary_10_1080_19490976_2021_1997296 crossref_primary_10_1016_j_envint_2024_108882 crossref_primary_10_2139_ssrn_3879082 crossref_primary_10_1099_jmm_0_001778 crossref_primary_10_1038_d41586_024_02740_8 crossref_primary_10_3389_fphar_2024_1276551 crossref_primary_10_1016_j_biopha_2022_113185 crossref_primary_10_1021_acs_molpharmaceut_2c01002 crossref_primary_10_1093_bfgp_elaa029 crossref_primary_10_1038_s41579_022_00681_5 crossref_primary_10_3389_fmicb_2021_650743 crossref_primary_10_1016_j_drudis_2020_11_037 crossref_primary_10_1186_s12915_020_00876_3 crossref_primary_10_3389_fmed_2020_00237 crossref_primary_10_1021_acschembio_3c00798 crossref_primary_10_3389_fmicb_2025_1480500 crossref_primary_10_1038_s41684_021_00724_z crossref_primary_10_1016_j_jcmgh_2024_05_003 crossref_primary_10_1007_s11126_019_09695_4 crossref_primary_10_1002_adma_202302551 crossref_primary_10_1038_s41564_022_01226_5 crossref_primary_10_3390_cancers14194796 crossref_primary_10_3390_pharmaceutics14020291 crossref_primary_10_3390_ijms22115576 crossref_primary_10_1016_j_phrs_2019_104456 crossref_primary_10_3390_ijms22052351 crossref_primary_10_3389_fmicb_2021_645500 crossref_primary_10_1016_j_foodres_2021_110819 crossref_primary_10_1016_j_aquaculture_2021_736885 crossref_primary_10_1097_MOL_0000000000000727 crossref_primary_10_1016_j_coemr_2021_03_003 crossref_primary_10_1016_j_cbpc_2022_109496 crossref_primary_10_1038_s41589_023_01369_4 crossref_primary_10_1007_s13238_020_00697_8 crossref_primary_10_1016_j_cotox_2019_07_001 crossref_primary_10_1016_j_jconrel_2022_10_043 crossref_primary_10_1038_d41586_019_02853_5 crossref_primary_10_1007_s13318_023_00874_0 crossref_primary_10_1016_j_drudis_2021_08_010 crossref_primary_10_18097_BMCRM00146 crossref_primary_10_3389_fmicb_2022_880118 crossref_primary_10_1016_j_jare_2021_10_004 crossref_primary_10_3390_metabo13050674 crossref_primary_10_1038_s41380_021_01201_2 crossref_primary_10_7554_eLife_50845 crossref_primary_10_12793_tcp_2020_28_e3 crossref_primary_10_1016_j_marpolbul_2021_112220 crossref_primary_10_1080_1744666X_2019_1656528 crossref_primary_10_1038_s41419_021_03829_y crossref_primary_10_1093_bib_bbad168 crossref_primary_10_1038_s41586_024_07336_w crossref_primary_10_1093_gbe_evab116 crossref_primary_10_1126_scitranslmed_adg8357 crossref_primary_10_1038_s41598_024_72225_1 crossref_primary_10_1016_j_ebiom_2019_05_009 crossref_primary_10_1111_cts_12722 crossref_primary_10_1111_1462_2920_14919 crossref_primary_10_1016_j_foodres_2025_115930 crossref_primary_10_1038_s41564_024_01853_0 crossref_primary_10_1016_j_cbpc_2024_109904 crossref_primary_10_1186_s40168_020_00912_y crossref_primary_10_1007_s10620_020_06119_3 crossref_primary_10_1016_j_semcancer_2020_06_006 crossref_primary_10_1088_2752_5724_ac48a3 crossref_primary_10_1016_j_ymeth_2023_12_007 crossref_primary_10_1038_s41587_024_02524_5 crossref_primary_10_1021_acs_jcim_1c00948 crossref_primary_10_1016_j_dmpk_2023_100532 crossref_primary_10_1016_j_chom_2021_12_003 crossref_primary_10_1016_j_sbi_2023_102567 crossref_primary_10_1016_j_apsb_2019_12_001 crossref_primary_10_1016_j_chom_2021_12_008 crossref_primary_10_3389_fphar_2020_00278 crossref_primary_10_1016_j_cell_2020_05_001 crossref_primary_10_1016_j_ecoenv_2024_115993 crossref_primary_10_1016_j_molcel_2020_03_006 crossref_primary_10_1093_cvr_cvz346 crossref_primary_10_1016_j_xcrm_2023_101153 crossref_primary_10_1371_journal_ppat_1009024 crossref_primary_10_1016_j_ejps_2021_105812 crossref_primary_10_1002_admt_202400434 crossref_primary_10_1016_j_bbr_2020_112886 crossref_primary_10_1016_j_phymed_2023_154899 crossref_primary_10_1016_j_crmeth_2021_100137 crossref_primary_10_1093_toxsci_kfz166 crossref_primary_10_1002_adma_202300977 crossref_primary_10_1007_s11428_021_00740_0 crossref_primary_10_3390_jcm10010005 crossref_primary_10_1080_1062936X_2023_2214375 crossref_primary_10_3390_biomedicines12081716 crossref_primary_10_1186_s42523_020_00036_6 crossref_primary_10_1016_j_biotechadv_2023_108272 crossref_primary_10_1016_j_cell_2024_08_037 crossref_primary_10_1038_s41591_019_0544_x crossref_primary_10_1016_j_cell_2024_08_038 crossref_primary_10_1007_s00281_020_00798_w crossref_primary_10_1128_msystems_01484_21 crossref_primary_10_1016_j_phymed_2021_153656 crossref_primary_10_1146_annurev_med_080719_091604 crossref_primary_10_1038_s41522_023_00402_7 crossref_primary_10_2217_pme_2020_0077 crossref_primary_10_33590_emj_CSEB2440 crossref_primary_10_3390_ijms22147692 crossref_primary_10_1021_acs_est_3c03595 crossref_primary_10_1111_petr_13866 crossref_primary_10_1080_19490976_2024_2360233 crossref_primary_10_1080_03602532_2023_2197178 crossref_primary_10_1016_j_micpath_2021_105340 crossref_primary_10_1002_med_21805 crossref_primary_10_1016_j_jhazmat_2022_130509 crossref_primary_10_1038_s41582_022_00681_2 crossref_primary_10_3389_fphar_2020_00390 crossref_primary_10_1016_j_aninu_2024_08_003 crossref_primary_10_1007_s00213_023_06489_2 crossref_primary_10_1126_science_abi9357 crossref_primary_10_3389_fphys_2019_01343 crossref_primary_10_1016_j_psj_2022_102267 crossref_primary_10_15252_msb_202010116 crossref_primary_10_1016_j_tips_2019_04_014 crossref_primary_10_1002_ijc_35298 crossref_primary_10_1124_dmd_121_000669 crossref_primary_10_3389_fphar_2021_758468 crossref_primary_10_1016_j_tice_2022_101747 crossref_primary_10_1128_mbio_01392_24 crossref_primary_10_1177_1091581819849833 crossref_primary_10_1021_acs_est_4c10434 crossref_primary_10_3390_microorganisms12102071 crossref_primary_10_2139_ssrn_3927642 crossref_primary_10_1016_j_chemosphere_2023_138464 |
Cites_doi | 10.1371/journal.pbio.1002533 10.1002/tera.1420440209 10.1038/nature11234 10.1111/j.1432-1033.1975.tb03925.x 10.1073/pnas.1102938108 10.1016/j.cell.2017.03.041 10.1128/JB.182.22.6339-6346.2000 10.1016/j.chom.2009.08.003 10.1016/j.str.2008.03.017 10.1016/j.cell.2017.03.045 10.1093/nar/gkw1017 10.1007/PL00008711 10.1093/bioinformatics/bti123 10.1016/0006-2952(94)00543-U 10.1208/s12248-009-9144-x 10.3109/00498258409151481 10.1016/S0378-1119(96)00674-9 10.1002/bdd.1994 10.1016/0041-008X(77)90108-9 10.1016/j.chom.2013.12.007 10.1097/00008571-199702000-00005 |
ContentType | Journal Article |
Copyright | Copyright © 2019 by the American Association for the Advancement of Science Copyright © 2019, American Association for the Advancement of Science. Copyright © 2019, American Association for the Advancement of Science |
Copyright_xml | – notice: Copyright © 2019 by the American Association for the Advancement of Science – notice: Copyright © 2019, American Association for the Advancement of Science. – notice: Copyright © 2019, American Association for the Advancement of Science |
DBID | AAYXX CITATION CGR CUY CVF ECM EIF NPM 7QF 7QG 7QL 7QP 7QQ 7QR 7SC 7SE 7SN 7SP 7SR 7SS 7T7 7TA 7TB 7TK 7TM 7U5 7U9 8BQ 8FD C1K F28 FR3 H8D H8G H94 JG9 JQ2 K9. KR7 L7M L~C L~D M7N P64 RC3 7X8 5PM |
DOI | 10.1126/science.aat9931 |
DatabaseName | CrossRef Medline MEDLINE MEDLINE (Ovid) MEDLINE MEDLINE PubMed Aluminium Industry Abstracts Animal Behavior Abstracts Bacteriology Abstracts (Microbiology B) Calcium & Calcified Tissue Abstracts Ceramic Abstracts Chemoreception Abstracts Computer and Information Systems Abstracts Corrosion Abstracts Ecology Abstracts Electronics & Communications Abstracts Engineered Materials Abstracts Entomology Abstracts (Full archive) Industrial and Applied Microbiology Abstracts (Microbiology A) Materials Business File Mechanical & Transportation Engineering Abstracts Neurosciences Abstracts Nucleic Acids Abstracts Solid State and Superconductivity Abstracts Virology and AIDS Abstracts METADEX Technology Research Database Environmental Sciences and Pollution Management ANTE: Abstracts in New Technology & Engineering Engineering Research Database Aerospace Database Copper Technical Reference Library AIDS and Cancer Research Abstracts Materials Research Database ProQuest Computer Science Collection ProQuest Health & Medical Complete (Alumni) Civil Engineering Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Algology Mycology and Protozoology Abstracts (Microbiology C) Biotechnology and BioEngineering Abstracts Genetics Abstracts MEDLINE - Academic PubMed Central (Full Participant titles) |
DatabaseTitle | CrossRef MEDLINE Medline Complete MEDLINE with Full Text PubMed MEDLINE (Ovid) Materials Research Database Technology Research Database Computer and Information Systems Abstracts – Academic Mechanical & Transportation Engineering Abstracts Nucleic Acids Abstracts ProQuest Computer Science Collection Computer and Information Systems Abstracts ProQuest Health & Medical Complete (Alumni) Materials Business File Environmental Sciences and Pollution Management Aerospace Database Copper Technical Reference Library Engineered Materials Abstracts Genetics Abstracts Bacteriology Abstracts (Microbiology B) Algology Mycology and Protozoology Abstracts (Microbiology C) AIDS and Cancer Research Abstracts Chemoreception Abstracts Industrial and Applied Microbiology Abstracts (Microbiology A) Advanced Technologies Database with Aerospace ANTE: Abstracts in New Technology & Engineering Civil Engineering Abstracts Aluminium Industry Abstracts Virology and AIDS Abstracts Electronics & Communications Abstracts Ceramic Abstracts Ecology Abstracts Neurosciences Abstracts METADEX Biotechnology and BioEngineering Abstracts Computer and Information Systems Abstracts Professional Entomology Abstracts Animal Behavior Abstracts Solid State and Superconductivity Abstracts Engineering Research Database Calcium & Calcified Tissue Abstracts Corrosion Abstracts MEDLINE - Academic |
DatabaseTitleList | MEDLINE - Academic Materials Research Database CrossRef MEDLINE |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database – sequence: 2 dbid: EIF name: MEDLINE url: https://proxy.k.utb.cz/login?url=https://www.webofscience.com/wos/medline/basic-search sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Sciences (General) Biology |
EISSN | 1095-9203 |
EndPage | 600 |
ExternalDocumentID | PMC6533120 30733391 10_1126_science_aat9931 26588160 |
Genre | Research Support, Non-U.S. Gov't Journal Article Research Support, N.I.H., Extramural |
GrantInformation_xml | – fundername: NIGMS NIH HHS grantid: R35 GM118159 – fundername: NIGMS NIH HHS grantid: DP2 GM105456 – fundername: NIAID NIH HHS grantid: U01 AI124275 |
GroupedDBID | --- --Z -DZ -ET -~X .-4 ..I .55 .DC 08G 0R~ 0WA 123 18M 2FS 2KS 2WC 2XV 34G 36B 39C 3R3 53G 5RE 66. 6OB 6TJ 7X2 7~K 85S 8F7 AABCJ AACGO AAIKC AAMNW AANCE AAWTO ABBHK ABDBF ABDEX ABDQB ABEFU ABIVO ABJNI ABOCM ABPLY ABPPZ ABQIJ ABTLG ABWJO ABZEH ACBEA ACBEC ACGFO ACGFS ACGOD ACIWK ACMJI ACNCT ACPRK ACQOY ACUHS ADDRP ADUKH ADXHL AEGBM AENEX AETEA AEUPB AEXZC AFBNE AFFDN AFFNX AFHKK AFQFN AFRAH AGFXO AGNAY AGSOS AHMBA AIDAL AIDUJ AJGZS ALIPV ALMA_UNASSIGNED_HOLDINGS ALSLI ASPBG AVWKF BKF BLC C45 CS3 DB2 DCCCD DU5 EBS EJD EMOBN F5P FA8 FEDTE HZ~ I.T IAO IEA IGS IH2 IHR INH INR IOF IOV IPO IPSME IPY ISE JAAYA JBMMH JCF JENOY JHFFW JKQEH JLS JLXEF JPM JSG JST KCC L7B LSO LU7 M0P MQT MVM N9A NEJ NHB O9- OCB OFXIZ OGEVE OMK OVD P-O P2P PQQKQ PZZ QS- RHI RXW SA0 SC5 SJN TAE TEORI TN5 TWZ UBW UCV UHB UKR UMD UNMZH UQL USG VVN WH7 WI4 X7M XJF XZL Y6R YK4 YKV YNT YOJ YR2 YR5 YRY YSQ YV5 YWH YYP YZZ ZCA ZE2 ~02 ~G0 ~KM ~ZZ AAYXX ABCQX CITATION K-O 0B8 CGR CUY CVF ECM EIF ESX GX1 IGG NPM OK1 PKN RHF UIG VQA YCJ YIF YIN ZKG 7QF 7QG 7QL 7QP 7QQ 7QR 7SC 7SE 7SN 7SP 7SR 7SS 7T7 7TA 7TB 7TK 7TM 7U5 7U9 8BQ 8FD C1K F28 FR3 H8D H8G H94 JG9 JQ2 K9. KR7 L7M L~C L~D M7N P64 RC3 7X8 5PM |
ID | FETCH-LOGICAL-c509t-c24241a76427b273aef41d3184ca5e03f9df1ae4ca79e7c34308c06b3b1a1ee93 |
ISSN | 0036-8075 1095-9203 |
IngestDate | Thu Aug 21 13:44:57 EDT 2025 Fri Jul 11 03:14:48 EDT 2025 Fri Jul 25 19:10:37 EDT 2025 Wed Feb 19 02:31:25 EST 2025 Tue Jul 01 01:51:29 EDT 2025 Thu Apr 24 22:53:37 EDT 2025 Thu Jul 03 21:42:42 EDT 2025 |
IsDoiOpenAccess | false |
IsOpenAccess | true |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 6427 |
Language | English |
License | Copyright © 2019, American Association for the Advancement of Science. |
LinkModel | OpenURL |
MergedId | FETCHMERGED-LOGICAL-c509t-c24241a76427b273aef41d3184ca5e03f9df1ae4ca79e7c34308c06b3b1a1ee93 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 These authors contributed equally to this work. Author Contributions: M.Z. and A.L.G. conceived and initiated the project; M.Z. performed the experiments; R.W. performed and analyzed the loss-of-function screen; M.Z. and M.Z.K. analyzed the data. M.Z.K. performed statistical analyses, developed in silico models, and prepared graphical illustrations; M.Z., M.Z.K. and A.L.G. wrote the manuscript. |
ORCID | 0000-0001-7599-3471 0000-0001-6021-1246 0000-0002-5797-3589 0000-0001-9616-3303 |
OpenAccessLink | https://www.ncbi.nlm.nih.gov/pmc/articles/6533120 |
PMID | 30733391 |
PQID | 2177203847 |
PQPubID | 1256 |
PageCount | 1 |
ParticipantIDs | pubmedcentral_primary_oai_pubmedcentral_nih_gov_6533120 proquest_miscellaneous_2183642932 proquest_journals_2177203847 pubmed_primary_30733391 crossref_citationtrail_10_1126_science_aat9931 crossref_primary_10_1126_science_aat9931 jstor_primary_26588160 |
ProviderPackageCode | CITATION AAYXX |
PublicationCentury | 2000 |
PublicationDate | 2019-02-08 |
PublicationDateYYYYMMDD | 2019-02-08 |
PublicationDate_xml | – month: 02 year: 2019 text: 2019-02-08 day: 08 |
PublicationDecade | 2010 |
PublicationPlace | United States |
PublicationPlace_xml | – name: United States – name: Washington |
PublicationTitle | Science (American Association for the Advancement of Science) |
PublicationTitleAlternate | Science |
PublicationYear | 2019 |
Publisher | American Association for the Advancement of Science The American Association for the Advancement of Science |
Publisher_xml | – name: American Association for the Advancement of Science – name: The American Association for the Advancement of Science |
References | e_1_3_2_27_2 e_1_3_2_28_2 e_1_3_2_20_2 e_1_3_2_21_2 e_1_3_2_22_2 e_1_3_2_23_2 e_1_3_2_24_2 Wilkins M. R. (e_1_3_2_25_2) 1999; 112 Okuda H. (e_1_3_2_26_2) 1998; 287 Nishiyama T. (e_1_3_2_4_2) 2000; 57 e_1_3_2_9_2 e_1_3_2_15_2 e_1_3_2_8_2 e_1_3_2_16_2 e_1_3_2_7_2 e_1_3_2_17_2 e_1_3_2_6_2 e_1_3_2_18_2 e_1_3_2_19_2 Desgranges C. (e_1_3_2_5_2) 1986; 46 e_1_3_2_10_2 e_1_3_2_11_2 e_1_3_2_12_2 e_1_3_2_3_2 e_1_3_2_13_2 e_1_3_2_2_2 e_1_3_2_14_2 31551561 - Nature. 2019 Sep;573(7775):615-616 |
References_xml | – ident: e_1_3_2_15_2 – ident: e_1_3_2_3_2 doi: 10.1371/journal.pbio.1002533 – ident: e_1_3_2_13_2 doi: 10.1002/tera.1420440209 – ident: e_1_3_2_7_2 doi: 10.1038/nature11234 – ident: e_1_3_2_20_2 – ident: e_1_3_2_10_2 doi: 10.1111/j.1432-1033.1975.tb03925.x – ident: e_1_3_2_16_2 doi: 10.1073/pnas.1102938108 – ident: e_1_3_2_23_2 doi: 10.1016/j.cell.2017.03.041 – ident: e_1_3_2_14_2 doi: 10.1128/JB.182.22.6339-6346.2000 – ident: e_1_3_2_9_2 doi: 10.1016/j.chom.2009.08.003 – ident: e_1_3_2_17_2 doi: 10.1016/j.str.2008.03.017 – ident: e_1_3_2_19_2 doi: 10.1016/j.cell.2017.03.045 – ident: e_1_3_2_28_2 doi: 10.1093/nar/gkw1017 – ident: e_1_3_2_6_2 doi: 10.1007/PL00008711 – ident: e_1_3_2_24_2 doi: 10.1093/bioinformatics/bti123 – ident: e_1_3_2_18_2 doi: 10.1016/0006-2952(94)00543-U – volume: 46 start-page: 1094 year: 1986 ident: e_1_3_2_5_2 article-title: Effect of (E)-5-(2-bromovinyl)uracil on the catabolism and antitumor activity of 5-fluorouracil in rats and leukemic mice publication-title: Cancer Res. – ident: e_1_3_2_2_2 doi: 10.1208/s12248-009-9144-x – ident: e_1_3_2_12_2 doi: 10.3109/00498258409151481 – ident: e_1_3_2_21_2 doi: 10.1016/S0378-1119(96)00674-9 – ident: e_1_3_2_11_2 doi: 10.1002/bdd.1994 – volume: 112 start-page: 531 year: 1999 ident: e_1_3_2_25_2 article-title: Protein identification and analysis tools in the ExPASy server publication-title: Methods Mol. Biol. – ident: e_1_3_2_27_2 doi: 10.1016/0041-008X(77)90108-9 – ident: e_1_3_2_22_2 doi: 10.1016/j.chom.2013.12.007 – volume: 287 start-page: 791 year: 1998 ident: e_1_3_2_26_2 article-title: A possible mechanism of eighteen patient deaths caused by interactions of sorivudine, a new antiviral drug, with oral 5-fluorouracil prodrugs publication-title: J. Pharmacol. Exp. Ther. – ident: e_1_3_2_8_2 doi: 10.1097/00008571-199702000-00005 – volume: 57 start-page: 899 year: 2000 ident: e_1_3_2_4_2 article-title: Mechanism-based inactivation of human dihydropyrimidine dehydrogenase by (E)-5-(2-bromovinyl)uracil in the presence of NADPH publication-title: Mol. Pharmacol. – reference: 31551561 - Nature. 2019 Sep;573(7775):615-616 |
SSID | ssj0009593 |
Score | 2.6649568 |
Snippet | Anything humans swallow is exposed to the foraging and transforming activities of the gut microbiota. This applies to therapeutic drugs as well as food... The gut microbiota is implicated in the metabolism of many medical drugs, with consequences for interpersonal variation in drug efficacy and toxicity. However,... Off-target drug metabolismAnything humans swallow is exposed to the foraging and transforming activities of the gut microbiota. This applies to therapeutic... |
SourceID | pubmedcentral proquest pubmed crossref jstor |
SourceType | Open Access Repository Aggregation Database Index Database Enrichment Source Publisher |
StartPage | 600 |
SubjectTerms | Absorption Animal models Animal tissues Animals Antidepressants Antiviral agents Bacteroides thetaiotaomicron - enzymology Bacteroides thetaiotaomicron - genetics Benzodiazepines Bioavailability Biocompatibility Biological Availability Biotransformation Bromodeoxyuridine - analogs & derivatives Bromodeoxyuridine - pharmacokinetics Bromodeoxyuridine - toxicity Clonazepam Clonazepam - pharmacokinetics Compartments Computer applications Computer simulation Conversion Digestive system Drug efficacy Drug metabolism Drugs Effectiveness Enzymes Exposure Food Gastrointestinal Microbiome Gastrointestinal tract Genetic transformation Genetics Germ-Free Life Germfree Gnotobiotic Gnotobiotics Health services In vivo methods and tests Intestinal microflora Intestine Kinetics Medical treatment Metabolism Metabolites Mice Microbiomes Microbiota Microorganisms Narcotics Nucleoside analogs Nucleosides Organic chemistry Oxidation Pharmacokinetics Pharmacology Physiological effects RESEARCH ARTICLE SUMMARY Toxicity Xenobiotics |
Title | Separating host and microbiome contributions to drug pharmacokinetics and toxicity |
URI | https://www.jstor.org/stable/26588160 https://www.ncbi.nlm.nih.gov/pubmed/30733391 https://www.proquest.com/docview/2177203847 https://www.proquest.com/docview/2183642932 https://pubmed.ncbi.nlm.nih.gov/PMC6533120 |
Volume | 363 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV3db9MwELdKJyReEBsMAgMZiYehKZUdp_l47IAx8fUAmzTxEjmJU6LSZNpSBPxJ_JWcY8dxqlYavFRt_KEmv4vvzr77HUIv_LgIGNjhbp5T7vphPnVTnsWuX0ScBTH3SRub8_FTcHruv7uYXoxGf6yopVWTTrLfG_NK_gdVuAa4yizZf0DWTAoX4DvgC5-AMHzeCOMvQjF3g7cvkzXag4BlqaiVljoMXdezaokc8qvV_OhSk1UvwL40HM1N_bPMymZwxtu99mCDmnMdC00ToDhTYQRdVIEeZm0xfC3l7vhSl2O2A_UHje77es5zIX5wnURU9ipDzLvhUh4WC9Pytq5zvYmrYjOPPkzsnQyZPOW5JLJXZ02OrHSTWpCJrCXpEWav2EyviUo0wYMKNysDq3ylmHDegC1Ge73XnfWvqUMTpNi6R16Q6AkSPcEttOOBS-KN0c7s-PXxyVaKZ00kZaVodf9hYAOpMNhNDs56nK5l-JzdQ3e1x4JnSvx20UhUe-i2qmH6aw_taryv8aGmMH95H33uJRNLycQgY7iXTDyQTNzUWEomXpfMdlQnmQ_Q-cmbs1enrq7e4WZghDZuJhOPKA8lPCkYyVwUPs1BhfgZnwrCijgvKBfwK4xFmDGfkSgjQcpSyqkQMdtH46quxCOEwe2NClak0lj3A-LxqVfQjKUeiVkUxtRBk-55JpmmtpcVVr4nWzB00KEZcKlYXbZ33W8BMv08sNkjGhAHHXSIJXpNuE7AwZdxDWDyOei5aYYVWx7D8UrUK9knYvBQwHFy0EMFsJlcalzG5B2FA-hNB8kGP2ypym8tK3wAjhv1yOOb39oTdKd_DQ_QuLlaiadgYjfpMy3bfwEyLdqY |
linkProvider | EBSCOhost |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Separating+host+and+microbiome+contributions+to+drug+pharmacokinetics+and+toxicity&rft.jtitle=Science+%28American+Association+for+the+Advancement+of+Science%29&rft.au=Zimmermann%2C+Michael&rft.au=Zimmermann-Kogadeeva%2C+Maria&rft.au=Wegmann%2C+Rebekka&rft.au=Goodman%2C+Andrew+L.&rft.date=2019-02-08&rft.issn=0036-8075&rft.eissn=1095-9203&rft.volume=363&rft.issue=6427&rft_id=info:doi/10.1126%2Fscience.aat9931&rft.externalDBID=n%2Fa&rft.externalDocID=10_1126_science_aat9931 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0036-8075&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0036-8075&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0036-8075&client=summon |