A few commonly used non-antibiotic drugs have recently been associated with changes in gut microbiome composition, but the extent of this phenomenon is unknown. Here, we screened more than 1,000 marketed drugs against 40 representative gut bacterial strains, and found that 24% of the drugs with human targets, including members of all therapeutic classes, inhibited the growth of at least one strain in vitro. Particular classes, such as the chemically diverse antipsychotics, were overrepresented in this group. The effects of human-targeted drugs on gut bacteria are reflected on their antibiotic-like side effects in humans and are concordant with existing human cohort studies. Susceptibility to antibiotics and human-targeted drugs correlates across bacterial species, suggesting common resistance mechanisms, which we verified for some drugs. The potential risk of non-antibiotics promoting antibiotic resistance warrants further exploration. Our results provide a resource for future research on drug–microbiome interactions, opening new paths for side effect control and drug repurposing, and broadening our view of antibiotic resistance.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.

from $8.99

All prices are NET prices.


  1. 1.

    , & Intestinal microbiota in health and disease. Nature 535, 47 (2016)

  2. 2.

    et al. Disentangling type 2 diabetes and metformin treatment signatures in the human gut microbiota. Nature 528, 262–266 (2015)

  3. 3.

    et al. Proton pump inhibitors affect the gut microbiome. Gut 65, 740–748 (2016)

  4. 4.

    et al. Proton pump inhibitors alter the composition of the gut microbiota. Gut 65, 749–756 (2016)

  5. 5.

    & The influence of non-steroidal anti-inflammatory drugs on the gut microbiome. Clin. Microbiol. Infect. 22, 171–179 (2016)

  6. 6.

    , , , & Interaction between atypical antipsychotics and the gut microbiome in a bipolar disease cohort. Pharmacotherapy 37, 261–267 (2017)

  7. 7.

    et al. Population-level analysis of gut microbiome variation. Science 352, 560–564 (2016)

  8. 8.

    et al. Nutritional preferences of the human gut bacteria reveal their metabolic idiosyncasies. Nat. Microbiol. (2018)

  9. 9.

    et al. Combinations of antibiotics and nonantibiotic drugs enhance antimicrobial efficacy. Nat. Chem. Biol. 7, 348–350 (2011)

  10. 10.

    , , & Bacterial uptake of aminoglycoside antibiotics. Microbiol. Rev. 51, 439–457 (1987)

  11. 11.

    Antibiotic use and its consequences for the normal microbiome. Science 352, 544–545 (2016)

  12. 12.

    , & Imidazoles as promising scaffolds for antibacterial activity: a review. Mini Rev. Med. Chem. 13, 1812–1835 (2013)

  13. 13.

    et al. Auranofin exerts broad-spectrum bactericidal activities by targeting thiol-redox homeostasis. Proc. Natl Acad. Sci. USA 112, 4453–4458 (2015)

  14. 14.

    et al. Antagonism screen for inhibitors of bacterial cell wall biogenesis uncovers an inhibitor of undecaprenyl diphosphate synthase. Proc. Natl Acad. Sci. USA 112, 11048–11053 (2015)

  15. 15.

    , , , & Machine learning meta-analysis of large metagenomic datasets: tools and biological insights. PLOS Comput. Biol. 12, e1004977 (2016)

  16. 16.

    , , & From dietary fiber to host physiology: short-chain fatty acids as key bacterial metabolites. Cell 165, 1332–1345 (2016)

  17. 17.

    et al. Enterotypes of the human gut microbiome. Nature 473, 174–180 (2011)

  18. 18.

    , & Gut biogeography of the bacterial microbiota. Nat. Rev. Microbiol. 14, 20–32 (2016)

  19. 19.

    , , & Supersaturation and precipitation of posaconazole upon entry in the upper small intestine in humans. J. Pharm. Sci. 105, 2677–2684 (2016)

  20. 20.

    , & Metformin and the intestine. Diabetologia 51, 1552–1553 (2008)

  21. 21.

    et al. Genomic variation landscape of the human gut microbiome. Nature 493, 45–50 (2013)

  22. 22.

    , , & The SIDER database of drugs and side effects. Nucleic Acids Res. 44, D1075–D1079 (2016)

  23. 23.

    , & Antibacterial activities of antineoplastic agents. Antimicrob. Agents Chemother. 28, 437–439 (1985)

  24. 24.

    , , & Chemotherapy-induced modifications to gastrointestinal microflora: evidence and implications of change. Curr. Drug Metab. 10, 79–83 (2009)

  25. 25.

    & Phenothiazines as anti-tubercular agents: mechanistic insights and clinical implications. Expert Opin. Investig. Drugs 20, 1665–1676 (2011)

  26. 26.

    et al. The antipsychotic olanzapine interacts with the gut microbiome to cause weight gain in mouse. PLoS One 9, e115225 (2014)

  27. 27.

    , & The challenge of efflux-mediated antibiotic resistance in Gram-negative bacteria. Clin. Microbiol. Rev. 28, 337–418 (2015)

  28. 28.

    , & ESCMID Study Group on Antimicrobial Resistance in Anaerobic Bacteria Antimicrobial susceptibility of Bacteroides fragilis group isolates in Europe: 20 years of experience. Clin. Microbiol. Infect. 17, 371–379 (2011)

  29. 29.

    , & Chemical genetics in drug discovery. Curr. Op. Syst. Biol. 4, 35–42 (2017)

  30. 30.

    et al. NorM, a putative multidrug efflux protein, of Vibrio parahaemolyticus and its homolog in Escherichia coli. Antimicrob. Agents Chemother. 42, 1778–1782 (1998)

  31. 31.

    et al. Antibiotic susceptibility profiles of Escherichia coli strains lacking multidrug efflux pump genes. Antimicrob. Agents Chemother. 45, 1126–1136 (2001)

  32. 32.

    et al. Phenotypic landscape of a bacterial cell. Cell 144, 143–156 (2011)

  33. 33.

    , & New substrates on the block: clinically relevant resistances for EmrE and homologues. J. Bacteriol. 194, 6766–6770 (2012)

  34. 34.

    , , & Activation of multiple antibiotic resistance and binding of stress-inducible promoters by Escherichia coli Rob protein. J. Bacteriol. 177, 1655–1661 (1995)

  35. 35.

    & Identification of the rrmA gene encoding the 23S rRNA m1G745 methyltransferase in Escherichia coli and characterization of an m1G745-deficient mutant. J. Bacteriol. 180, 359–365 (1998)

  36. 36.

    , , & Reduction of polynitroaromatic compounds: the bacterial nitroreductases. FEMS Microbiol. Rev. 32, 474–500 (2008)

  37. 37.

    et al. Dihydrofolate reductase: x-ray structure of the binary complex with methotrexate. Science 197, 452–455 (1977)

  38. 38.

    et al. The microbiome of uncontacted Amerindians. Sci. Adv. 1, e1500183 (2015)

  39. 39.

    , , & The microbial pharmacists within us: a metagenomic view of xenobiotic metabolism. Nat. Rev. Microbiol. 14, 273–287 (2016)

  40. 40.

    et al. A tool named Iris for versatile high-throughput phenotyping in microorganisms. Nat. Microbiol. 2, 17014 (2017)

  41. 41.

    , & Cultivation-based multiplex phenotyping of human gut microbiota allows targeted recovery of previously uncultured bacteria. Nat. Commun. 5, 4714 (2014)

  42. 42.

    et al. Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice. Proc. Natl Acad. Sci. USA 108, 6252–6257 (2011)

  43. 43.

    et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010)

  44. 44.

    et al. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55–60 (2012)

  45. 45.

    Human Microbiome Project Consortium. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012)

  46. 46.

    et al. Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes. Nat. Biotechnol. 32, 822–828 (2014)

  47. 47.

    , , & Accurate and universal delineation of prokaryotic species. Nat. Methods 10, 881–884 (2013)

  48. 48.

    et al. MOCAT2: a metagenomic assembly, annotation and profiling framework. Bioinformatics 32, 2520–2523 (2016)

  49. 49.

    Bayesian estimation supersedes the t test. J. Exp. Psychol. Gen. 142, 573–603 (2013)

  50. 50.

    & Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. B 57, 289–300 (1995)

  51. 51.

    et al. STITCH 4: integration of protein-chemical interactions with user data. Nucleic Acids Res. 42, D401–D407 (2014)

  52. 52.

    et al. CART-a chemical annotation retrieval toolkit. Bioinformatics 32, 2869–2871 (2016)

  53. 53.

    et al. Quantification of gastrointestinal liquid volumes and distribution following a 240 mL dose of water in the fasted state. Mol. Pharm. 11, 3039–3047 (2014)

  54. 54.

    et al. DrugBank 4.0: shedding new light on drug metabolism. Nucleic Acids Res. 42, D1091–D1097 (2014)

  55. 55.

    & How to interpret a functional or motility test—colon transit study. J. Neurogastroenterol. Motil. 18, 94–99 (2012)

  56. 56.

    et al. Fasting and postprandial volumes of the undisturbed colon: normal values and changes in diarrhea-predominant irritable bowel syndrome measured using serial MRI. Neurogastroenterol. Motil. 26, 124–130 (2014)

  57. 57.

    & Setting and revising antibacterial susceptibility breakpoints. Clin. Microbiol. Rev. 20, 391–408 (2007)

  58. 58.

    , , , & Drug target identification using side-effect similarity. Science 321, 263–266 (2008)

  59. 59.

    et al. GenoBase: comprehensive resource database of Escherichia coli K-12. Nucleic Acids Res. 43, D606–D617 (2015)

  60. 60.

    et al. Identification of essential genes and synthetic lethal gene combinations in Escherichia coli K-12. Methods Mol. Biol. 1279, 45–65 (2015)

  61. 61.

    et al. Metformin alters the gut microbiome of individuals with treatment-naive type 2 diabetes, contributing to the therapeutic effects of the drug. Nat. Med. 23, 850–858 (2017)

  62. 62.

    et al. Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics. Curr. Pharm. Des. 12, 2111–2120 (2006)

  63. 63.

    et al. PubChem substance and compound databases. Nucleic Acids Res. 44, D1202–D1213 (2016)

Download references


We thank P. Beltrao (EBI), K. C. Huang (Stanford) and F. Cabreiro (UCL) for feedback on the manuscript; F. Rippmann (Merck KGaA) for pointing to the delayed onset of antipsychotics; S. Wicha (University of Hamburg) for discussions on drug concentrations; J. Overington (Medicines Discovery Catapult) for help with drug plasma concentrations, and members of all four laboratories for fruitful discussions (in particular T. Hodges for suggestions on the manuscript and M. Driessen for experimental support). We thank the EMBL mechanical workshop for the custom-made incubator. We acknowledge funding from EMBL and the Microbios grant (ERC-AdG-669830). L.M. and M.P. were supported by the EMBL Interdisciplinary Postdoc (EIPOD) programme under Marie Sklodowska Curie Actions COFUND (grant 291772). A.Te. and A.R.B. were supported by a Sofja Kovaleskaja Award of the Alexander von Humboldt Foundation to A.Ty.

Author information

Author notes

    • Mihaela Pruteanu

    Present address: Institute for Biology, Humboldt University Berlin, 10115 Berlin, Germany.

    • Lisa Maier
    • , Mihaela Pruteanu
    •  & Michael Kuhn

    These authors contributed equally to this work.


  1. European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany

    • Lisa Maier
    • , Mihaela Pruteanu
    • , Anja Telzerow
    • , Exene Erin Anderson
    • , Ana Rita Brochado
    • , Keith Conrad Fernandez
    •  & Athanasios Typas
  2. European Molecular Biology Laboratory, Structural and Computational Biology Unit, 69117 Heidelberg, Germany

    • Michael Kuhn
    • , Georg Zeller
    • , Kiran Raosaheb Patil
    • , Peer Bork
    •  & Athanasios Typas
  3. Graduate School of Biological Sciences, Nara Institute of Science and Technology, 630-0101 Ikoma, Japan

    • Hitomi Dose
    •  & Hirotada Mori
  4. Max-Delbrück-Centre for Molecular Medicine, 13125 Berlin, Germany

    • Peer Bork
  5. Molecular Medicine Partnership Unit, 69120 Heidelberg, Germany

    • Peer Bork
  6. Department of Bioinformatics, Biocenter, University of Würzburg, 97024 Würzburg, Germany.

    • Peer Bork


  1. Search for Lisa Maier in:

  2. Search for Mihaela Pruteanu in:

  3. Search for Michael Kuhn in:

  4. Search for Georg Zeller in:

  5. Search for Anja Telzerow in:

  6. Search for Exene Erin Anderson in:

  7. Search for Ana Rita Brochado in:

  8. Search for Keith Conrad Fernandez in:

  9. Search for Hitomi Dose in:

  10. Search for Hirotada Mori in:

  11. Search for Kiran Raosaheb Patil in:

  12. Search for Peer Bork in:

  13. Search for Athanasios Typas in:


The study was conceived by K.R.P., P.B. and A.Ty., designed by L.M., M.P., G.Z., A.R.B. and A.Ty., and supervised by K.R.P., P.B. and A.Ty. In vitro screening was established by M.P. and performed by L.M., M.P., A.Te. and K.C.F. Follow-up and validation experiments were conducted by L.M., M.P. and E.E.A. H.D. and H.M. constructed and provided the Transbac library. Data preprocessing was performed by M.K. and G.Z.; statistical analyses by M.K.; data curation by L.M., M.K. and E.E.A.; data interpretation by L.M., M.P., M.K., G.Z., K.R.P., P.B. and A.Ty. L.M., M.K., G.Z., K.R.P., P.B. and A.Ty. wrote the manuscript with input from M.P. and A.R.B.; L.M., M.K. and G.Z. designed figures with input from K.R.P., P.B. and A.Ty. All authors approved the final version for publication.

Competing interests

EMBL has filed two patent applications on repurposing compounds identified in this study for the treatment of infections and for modulating the composition of the gut microbiome, and on the use of the in vitro model of the human gut microbiome to study the impact of xenobiotics (Tentative European patent application numbers EP 18156520 and EP 18155278, respectively). Authors L.M., M.P., M.K., G.Z., K.R.P., P.B. and A.T. are listed as inventors.

Corresponding authors

Correspondence to Georg Zeller or Kiran Raosaheb Patil or Peer Bork or Athanasios Typas.

Reviewer Information Nature thanks K. Lewis, H. B. Nielsen, G. Wright and R. Xavier for their contribution to the peer review of this work.

Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Supplementary information

PDF files

  1. 1.

    Life Sciences Reporting Summary

  2. 2.

    Supplementary Information

    This file contains a Supplementary Discussion.

Excel files

  1. 1.

    Supplementary Table 1

    This file shows the compounds used in this study. Sheet 1 shows the compounds of the Prestwick Chemical Library, their assignment to therapeutic classes according to the ATC classification system, chemical and physical properties, single doses (which are half of the daily doses), plasma concentrations, estimated small intestine concentrations, route of excretion, estimated colon concentrations and conversion of the molar concentration of the screen (20 μM) into μg/ml. Sheet 2 shows the chemicals used in this study.

  2. 2.

    Supplementary Table 2

    This file contains the strains used in this study, their medium requirements and starting ODs for drug screening in 96- or 384-format.

  3. 3.

    Supplementary Table 3

    This file contains drugs with anticommensal activity in our screen. Sheet 1 shows the adjusted p-values for the impact of 1197 drugs on anaerobic growth of 40 human gut bacteria (see Methods). Sheet 2 shows the literature evidence and lowest measured MICs for antibacterial activity of the top 40 human-targeted drugs that affect more than 10 strains in our screen.

  4. 4.

    Supplementary Table 4

    This file contains IC25 determination which shows 25 selected drugs in a subset of up to 27 strains.

  5. 5.

    Supplementary Table 5

    This file contains the antibiotic-related side effects in human-targeted drugs (see Methods).

  6. 6.

    Supplementary Table 6

    This file contains the screen results of additionally screened strains (Figure 4), which shows the E. coli ΔtolC, its parental background (BW25113) and of B. fragilis HM-20 (NT5057) and B. uniformis HM-715 (NT5065).

About this article

Publication history







By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.