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...

Full description

Saved in:
Bibliographic Details
Published inScience (American Association for the Advancement of Science) Vol. 363; no. 6427; p. 600
Main Authors Zimmermann, Michael, Zimmermann-Kogadeeva, Maria, Wegmann, Rebekka, Goodman, Andrew L.
Format Journal Article
LanguageEnglish
Published United States American Association for the Advancement of Science 08.02.2019
The American Association for the Advancement of Science
Subjects
Online AccessGet 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