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HUANGFU Yifan, RAN Yuye, FENG Shuo, LI Jing. Comparison of bacterial and human drug metabolizing enzymes in database and prospect of influence of intestinal bacteria on drug metabolism[J]. Journal of China Pharmaceutical University, 2023, 54(1): 122-130. DOI: 10.11665/j.issn.1000-5048.20220705001
Citation: HUANGFU Yifan, RAN Yuye, FENG Shuo, LI Jing. Comparison of bacterial and human drug metabolizing enzymes in database and prospect of influence of intestinal bacteria on drug metabolism[J]. Journal of China Pharmaceutical University, 2023, 54(1): 122-130. DOI: 10.11665/j.issn.1000-5048.20220705001

Comparison of bacterial and human drug metabolizing enzymes in database and prospect of influence of intestinal bacteria on drug metabolism

Funds: This study was supported by the National Natural Science Foundation of China (No.32170062); the Project of Hunan Key Laboratory for Bioanalysis of Complex Matrix Samples (No.2017TP1037) and the Postgraduate Research & Practice Innovation Program of Jiangsu Province (No.3322200020)
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  • Received Date: July 04, 2022
  • Revised Date: January 31, 2023
  • This study focused on various databases and literatures related to drug metabolism, collated and analyzed the information related to bacterial and human drug metabolic enzymes, and compared the similarities and differences between the information included in the database of bacterial and human drug metabolic enzymes. Results found more bacterial drug metabolic enzymes than human drug metabolic enzymes (9 703 vs 964), but much less than the total number of bacterial enzymes in BRENDA database (9 703 vs 20 835 235), indicating that the influence of bacteria on drug metabolism could have been greatly underestimated, and that further systematic research is needed.We summarized the progress and shortcomings of the current research on the influence of intestinal flora on drug metabolism, and proposed a research idea, that is, to predict through artificial intelligence whether intestinal bacterial proteins have the ability to metabolize drugs, to verify their biological functions by in vitro/in vivo experiments and gene editing, and to establish a database of drug metabolic enzymes from intestinal bacteria with complete annotation functions, in an attempt to provide a solid theoretical basis for further exploration of the effects of intestinal flora on drug metabolism.
  • [1]
    . Gastroenterology,2021,160(2):524-537.
    [2]
    Witkowski M,Weeks TL,Hazen SL. Gut microbiota and cardiovascular disease[J]. Circ Res,2020,127(4):553-570.
    [3]
    Sepich-Poore GD,Zitvogel L,Straussman R,et al. The microbiome and human cancer[J]. Science,2021,371(6536):eabc4552.
    [4]
    van den Elsen LWJ,Garssen J,Burcelin R,et al. Shaping the gut microbiota by breastfeeding:the gateway to allergy prevention[J]?Front Pediatr,2019,7:47.
    [5]
    Generoso JS,Giridharan VV,Lee J,et al. The role of the microbiota-gut-brain axis in neuropsychiatric disorders[J]. Braz J Psychiatry,2021,43(3):293-305.
    [6]
    Agus A,Clément K,Sokol H. Gut microbiota-derived metabolites as central regulators in metabolic disorders[J]. Gut,2021,70(6):1174-1182.
    [7]
    Sharpton SR,Schnabl B,Knight R,et al. Current concepts,opportunities,and challenges of gut microbiome-based personalized medicine in nonalcoholic fatty liver disease[J]. Cell Metab,2021,33(1):21-32.
    [8]
    Vich Vila A,Collij V,Sanna S,et al. Impact of commonly used drugs on the composition and metabolic function of the gut microbiota[J]. Nat Commun,2020,11(1):362.
    [9]
    Tong XL,Xu J,Lian FM,et al. Structural alteration of gut microbiota during the amelioration of human type 2 diabetes with hyperlipidemia by metformin and a traditional Chinese herbal formula:a multicenter,randomized,open label clinical trial[J]. mBio,2018,9(3):e02392-e02317.
    [10]
    Qin JJ,Li RQ,Raes J,et al. A human gut microbial gene catalogue established by metagenomic sequencing[J]. Nature,2010,464(7285):59-65.
    [11]
    Spanogiannopoulos P,Bess EN,Carmody RN,et al. The microbial pharmacists within us:a metagenomic view of xenobiotic metabolism[J]. Nat Rev Microbiol,2016,14(5):273-287.
    [12]
    Guthrie L,Gupta S,Daily J,et al. Human microbiome signatures of differential colorectal cancer drug metabolism[J]. NPJ Biofilms Microbiomes,2017,3:27.
    [13]
    van Kessel SP,Frye AK,El-Gendy AO,et al. Gut bacterial tyrosine decarboxylases restrict levels of levodopa in the treatment of Parkinson''s disease[J]. Nat Commun,2019,10(1):310.
    [14]
    Maini Rekdal V,Bess EN,Bisanz JE,et al. Discovery and inhibition of an interspecies gut bacterial pathway for Levodopa metabolism[J]. Science,2019,364(6445):eaau6323.
    [15]
    Maier LS,Pruteanu M,Kuhn M,et al. Extensive impact of non-antibiotic drugs on human gut bacteria[J]. Nature,2018,555(7698):623-628.
    [16]
    Zimmermann M,Zimmermann-Kogadeeva M,Wegmann R,et al. Mapping human microbiome drug metabolism by gut bacteria and their genes[J]. Nature,2019,570(7762):462-467.
    [17]
    Weersma RK,Zhernakova A,Fu JY. Interaction between drugs and the gut microbiome[J]. Gut,2020,69(8):1510-1519.
    [18]
    Clarke G,Sandhu KV,Griffin BT,et al. Gut reactions:breaking down xenobiotic-microbiome interactions[J]. Pharmacol Rev,2019,71(2):198-224.
    [19]
    Klünemann M,Andrejev S,Blasche S,et al. Bioaccumulation of therapeutic drugs by human gut bacteria[J]. Nature,2021,597(7877):533-538.
    [20]
    Uechi K,Tada T,Sawachi Y,et al. A carbapenem-resistant clinical isolate of Aeromonas hydrophila in Japan harbouring an acquired gene encoding GES-24 β-lactamase[J]. J Med Microbiol,2018,67(11):1535-1537.
    [21]
    Dingsdag SA,Hunter N. Metronidazole:an update on metabolism,structure-cytotoxicity and resistance mechanisms[J]. J Antimicrob Chemother,2018,73(2):265-279.
    [22]
    Boddu RS,Perumal O,Divakar K. Microbial nitroreductases:a versatile tool for biomedical and environmental applications[J]. Biotechnol Appl Biochem,2021,68(6):1518-1530.
    [23]
    Day MA,Jarrom D,Christofferson AJ,et al. The structures of E. coli NfsA bound to the antibiotic nitrofurantoin; to 1,4-benzoquinone and to FMN[J]. Biochem J,2021,478(13):2601-2617.
    [24]
    Mao BY,Li DY,Zhao JX,et al. In vitro fermentation of lactulose by human gut bacteria[J]. J Agric Food Chem,2014,62(45):10970-10977.
    [25]
    Wang PP,Jia YF,Wu RR,et al. Human gut bacterial β-glucuronidase inhibition:an emerging approach to manage medication therapy[J]. Biochem Pharmacol,2021,190:114566.
    [26]
    Kumar K,Dhoke GV,Sharma AK,et al. Mechanistic elucidation of amphetamine metabolism by tyramine oxidase from human gut microbiota using molecular dynamics simulations[J]. J Cell Biochem,2019,120(7):11206-11215.
    [27]
    Haiser HJ,Seim KL,Balskus EP,et al. Mechanistic insight into digoxin inactivation by Eggerthella lenta augments our understanding of its pharmacokinetics[J]. Gut Microbes,2014,5(2):233-238.
    [28]
    Gomes AC,Hoffmann C,Mota JF. The human gut microbiota:metabolism and perspective in obesity[J]. Gut Microbes,2018,9(4):308-325.
    [29]
    Wang QW,Ma BB,Fushinobu S,et al. Regio- and stereoselective hydroxylation of testosterone by a novel cytochrome P450 154C2 from Streptomyces avermitilis[J]. Biochem Biophys Res Commun,2020,522(2):355-361.
    [30]
    Rabelo-Fernandez RJ,Santiago-Morales K,Morales-Vale L,et al. The metagenome of Caracolus marginella gut microbiome using culture independent approaches and shotgun sequencing[J]. Data Brief,2018,16:501-505.
    [31]
    Crouwel F,Buiter HJC,de Boer NK. Gut microbiota-driven drug metabolism in inflammatory bowel disease[J]. J Crohns Colitis,2020,15(2):307-315.
    [32]
    Yan A,Culp E,Perry J,et al. Transformation of the anticancer drug doxorubicin in the human gut microbiome[J]. ACS Infect Dis,2018,4(1):68-76.
    [33]
    Yang GY,Ge SF,Singh R,et al. Glucuronidation:driving factors and their impact on glucuronide disposition[J]. Drug MeTable Rev,2017,49(2):105-138.
    [34]
    Lee SH,Choi N,Sung JH. Pharmacokinetic and pharmacodynamic insights from microfluidic intestine-on-a-chip models[J]. Expert Opin Drug MeTable Toxicol,2019,15(12):1005-1019.
    [35]
    Sun PN,Zhou XL,Farnworth SL,et al. Modeling human liver biology using stem cell-derived hepatocytes[J]. Int J Mol Sci,2013,14(11):22011-22021.
    [36]
    Lee SY,Kim D,Lee SH,et al. Microtechnology-based in vitro models:Mimicking liver function and pathophysiology[J]. APL Bioeng,2021,5(4):041505.
    [37]
    Chen SL,Li Z,Zhang SY,et al. Emerging biotechnology applications in natural product and synthetic pharmaceutical analyses[J]. Acta Pharm Sin B,2022,12(11):4075-4097.
    [38]
    Xie RP,Li JH,Wang JW,et al. DeepVF:a deep learning-based hybrid framework for identifying virulence factors using the stacking strategy[J]. Brief Bioinform,2021,22(3):bbaa125.
    [39]
    Zhang Z,Zhang Q,Wang T,et al. Assessment of global health risk of antibiotic resistance genes[J]. Nat Commun,2022,13(1):1553.
    [40]
    Kataria R,Khatkar A. Molecular docking,synthesis,kinetics study,structure-activity relationship and ADMET analysis of morin analogous as Helicobacter pylori urease inhibitors[J]. BMC Chem,2019,13(1):45.
    [41]
    Jumper J,Evans R,Pritzel A,et al. Highly accurate protein structure prediction with AlphaFold[J]. Nature,2021,596(7873):583-589.
    [42]
    McCoubrey LE,Thomaidou S,Elbadawi M,et al. Machine learning predicts drug metabolism and bioaccumulation by intestinal microbiota[J]. Pharmaceutics,2021,13(12):2001.
    [43]
    McCoubrey LE,Elbadawi M,Orlu M,et al. Machine learning uncovers adverse drug effects on intestinal bacteria[J]. Pharmaceutics,2021,13(7):1026.
    [44]
    Zimmermann M,Zimmermann-Kogadeeva M,Wegmann R,et al. Separating host and microbiome contributions to drug pharmacokinetics and toxicity[J]. Science,2019,363(6427):eaat9931.
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