The human gut microbiota has adapted to the presence of antimicrobial peptides (AMPs), which are ancient components of immune defence. Despite its medical importance, it has remained unclear whether AMP resistance genes in the gut microbiome are available for genetic exchange between bacterial species. Here, we show that AMP resistance and antibiotic resistance genes differ in their mobilization patterns and functional compatibilities with new bacterial hosts. First, whereas AMP resistance genes are widespread in the gut microbiome, their rate of horizontal transfer is lower than that of antibiotic resistance genes. Second, gut microbiota culturing and functional metagenomics have revealed that AMP resistance genes originating from phylogenetically distant bacteria have only a limited potential to confer resistance in Escherichia coli, an intrinsically susceptible species. Taken together, functional compatibility with the new bacterial host emerges as a key factor limiting the genetic exchange of AMP resistance genes. Finally, our results suggest that AMPs induce highly specific changes in the composition of the human microbiota, with implications for disease risks.

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Data availability

The GenBank accession nos. for the PacBio sequencing data are MH883365MH883616. 16S rRNA sequencing reads are available from the Sequence Read Archive (SRA) (BioProject PRJNA494380). All data generated or analysed during this study are included in this article and its Supplementary Information. For each figure, the availability of the analysed data is indicated in the legend. All accession numbers with information on the associated samples are provided as Supplementary Data.

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The authors thank D. Módos, D. Fazekas, K. Kovács, A. Tooming-Klunderud, J. Sóki and E. Urbán for technical support. This work was supported by the ‘Lendület’ programme of the Hungarian Academy of Sciences (B.P. and C.P.), the Wellcome Trust (B.P.), The European Research Council H2020-ERC-2014-CoG 648364 Resistance Evolution (C.P.), GINOP 2.3.2-15-2016-00014 (EVOMER, C.P. and B.P.), GINOP-2.3.2-15-2016-00020 (MolMedEx TUMORDNS, C.P.), GINOP-2.3.2-15-2016-00026 (iChamber, B.P.), the National Research, Development and Innovation Office, Hungary (NKFIH grant K120220, B.K.), NKFIH grants FK124254 (O.M.) and KH125616 (B.P.), and a PhD fellowship from the Boehringer Ingelheim Fonds (A.N.). B.K. holds a Bolyai Janos Scholarship. The Pacific Biosciences sequencing service was provided by the Norwegian Sequencing Centre, a national technology platform hosted by the University of Oslo and supported by the ‘Functional Genomics’ and ‘Infrastructure’ programs of the Research Council of Norway and the Southeastern Regional Health Authorities.

Author information

Author notes

  1. These authors contributed equally: Bálint Kintses, Orsolya Méhi, Eszter Ari.


  1. Synthetic and Systems Biology Unit, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary

    • Bálint Kintses
    • , Orsolya Méhi
    • , Eszter Ari
    • , Mónika Számel
    • , Ádám Györkei
    • , Pramod K. Jangir
    • , Ferenc Pál
    • , Gergely Fekete
    • , Roland Tengölics
    • , Ákos Nyerges
    • , Balázs Papp
    •  & Csaba Pál
  2. Department of Genetics, Eötvös Loránd University, Budapest, Hungary

    • Eszter Ari
    •  & Misshelle Bustamante
  3. Doctoral School in Biology, Faculty of Science and Informatics, University of Szeged, Szeged, Hungary

    • Mónika Számel
    • , Pramod K. Jangir
    •  & Ákos Nyerges
  4. SeqOmics Biotechnology Ltd, Mórahalom, Hungary

    • István Nagy
    • , Balázs Bálint
    •  & Bálint Márk Vásárhelyi
  5. Sequencing Platform, Institute of Biochemistry, Biological Research Centre of the Hungarian Academy of Sciences, Szeged, Hungary

    • István Nagy
  6. Hereditary Endocrine Tumors Research Group, Hungarian Academy of Sciences and Semmelweis University, Budapest, Hungary

    • István Likó
  7. 1st Department of Internal Medicine, Albert Szent-Györgyi Health Centre, University of Szeged, Szeged, Hungary

    • Anita Bálint
    •  & Tamás Molnár


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B.K. and C.P. conceived of the project. B.K., O.M., E.A., A.N., B.P. and C.P. planned the experiments and data analyses. O.M., M.S., P.K.J. and R.T. performed the experiments. I.N. performed Illumina sequencing. A.B. and T.M. were responsible for faecal sample collection. B.K., O.M., E.A., A.G., F.P., G.F., I.L., B.B., B.M.V and M.B. analysed the experimental data and carried out bioinformatic analyses. B.K., O.M., B.P. and C.P. wrote the manuscript.

Competing interests

B.M.V., B.B. and I.N. had consulting positions at SeqOmics Biotechnology Ltd at the time the study was conceived. SeqOmics Biotechnology Ltd was not directly involved in the design and execution of the experiments or in the writing of the manuscript. This does not alter the authors’ adherence to all the Nature policies on sharing data and materials. The other authors declare no competing interests.

Corresponding authors

Correspondence to Bálint Kintses or Balázs Papp or Csaba Pál.

Supplementary information

  1. Supplementary Information

    Supplementary Figures 1–13, Supplementary Table 5, Supplementary Table 8, Supplementary Table 9 and Supplementary Table 11.

  2. Reporting Summary

  3. Supplementary Data

    Accession numbers of contigs from PacBio sequencing and 16S rRNA sequences.

  4. Supplementary Table 1

    A comprehensive catalogue of previously reported AMP resistance genes, compiled based on literature mining, and antibiotic resistance genes obtained from the CARD database.

  5. Supplementary Table 2

    Identification of AMP- and antibiotic-resistance genes in the bacterial genome sequences from which the mobile gene pool was derived.

  6. Supplementary Table 3

    Characteristics of the transferred AMP- and antibiotic-resistance genes in the mobile gene pool.

  7. Supplementary Table 4

    Identification of AMP- and antibiotic-resistance genes associated with naturally occurring plasmids and ICEs in the human microbiota.

  8. Supplementary Table 6

    List of resistance contigs identified from the functional metagenomic selections of the uncultured microbiota with 12 AMPs and 11 small-molecule antibiotics (Supplementary Table 5).

  9. Supplementary Table 7

    Bacterial abundances in the untreated and AMP- and antibiotic-resistant microbiota at family and order levels, respectively. Abundances at order and family levels are presented on separate Excel sheets.

  10. Supplementary Table 10

    List of resistance contigs identified from the functional selection of the cultured microbiota with 5 AMPs and 5 small-molecule antibiotics (Supplementary Table 5).

  11. Supplementary Table 12

    Resistance gains in Escherichia coli and Salmonella enterica provided by a representative set of plasmids carrying AMP- and antibiotic-resistance contigs that were isolated in metagenomic screens.

  12. Supplementary Table 13

    List of primers used in this study.

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