Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries

Abstract

Antimicrobial resistance (AMR) in bacteria and associated human morbidity and mortality is increasing. The use of antimicrobials in livestock selects for AMR that can subsequently be transferred to humans. This flow of AMR between reservoirs demands surveillance in livestock and in humans. We quantified and characterized the acquired resistance gene pools (resistomes) of 181 pig and 178 poultry farms from nine European countries, sequencing more than 5,000 Gb of DNA using shotgun metagenomics. We quantified acquired AMR using the ResFinder database and a second database constructed for this study, consisting of AMR genes identified through screening environmental DNA. The pig and poultry resistomes were very different in abundance and composition. There was a significant country effect on the resistomes, more so in pigs than in poultry. We found higher AMR loads in pigs, whereas poultry resistomes were more diverse. We detected several recently described, critical AMR genes, including mcr-1 and optrA, the abundance of which differed both between host species and between countries. We found that the total acquired AMR level was associated with the overall country-specific antimicrobial usage in livestock and that countries with comparable usage patterns had similar resistomes. However, functionally determined AMR genes were not associated with total drug use.

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Fig. 1: Overview of AMR abundance and composition.
Fig. 2: Resistome clustering is influenced by both host animal and country.
Fig. 3: AMR genes differ in abundance between countries.
Fig. 4: Resistome alpha diversity and richness differ between animal host and countries.
Fig. 5: Taxonomic variation explains resistome variation.
Fig. 6: National veterinary AMU is associated with total metagenomic AMR.

References

  1. 1.

    Antimicrobial Resistance Global Report on Surveillance 2014 (WHO, 2014).

  2. 2.

    Aarestrup, F. M. The livestock reservoir for antimicrobial resistance: a personal view on changing patterns of risks, effects of interventions and the way forward. Phil. Trans. R. Soc. B 370, 20140085 (2015).

    Article  Google Scholar 

  3. 3.

    Chantziaras, I., Boyen, F., Callens, B. & Dewulf, J. Correlation between veterinary antimicrobial use and antimicrobial resistance in food-producing animals: a report on seven countries. J. Antimicrob. Chemother. 69, 827–834 (2014).

    CAS  Article  Google Scholar 

  4. 4.

    Dunlop, R. H. et al. Associations among antimicrobial drug treatments and antimicrobial resistance of fecal Escherichia coli of swine on 34 farrow-to-finish farms in Ontario, Canada. Prev. Vet. Med. 34, 283–305 (1998).

    CAS  Article  Google Scholar 

  5. 5.

    Aarestrup, F. M., Seyfarth, A. M., Emborg, H., Pedersen, K. & Bager, F. Effect of abolishment of the use of antimicrobial agents for growth promotion on occurrence of antimicrobial resistance in fecal enterococci from food animals in Denmark. Antimicrob. Agents Chemother. 45, 2054–2059 (2001).

    CAS  Article  Google Scholar 

  6. 6.

    Agersø, Y. & Aarestrup, F. M. Voluntary ban on cephalosporin use in Danish pig production has effectively reduced extended-spectrum cephalosporinase-producing Escherichia coli in slaughter pigs. J. Antimicrob. Chemother. 68, 569–572 (2013).

    Article  Google Scholar 

  7. 7.

    Dutil, L. et al. Ceftiofur resistance in Salmonella enterica serovar Heidelberg from chicken meat and humans, Canada. Emerg. Infect. Dis. 16, 48–54 (2010).

    Article  Google Scholar 

  8. 8.

    Dorado-García, A. et al. Quantitative assessment of antimicrobial resistance in livestock during the course of a nationwide antimicrobial use reduction in the Netherlands. J. Antimicrob. Chemother. 71, 3607–3619 (2016).

    Article  Google Scholar 

  9. 9.

    Aarestrup, F. M. et al. Resistance to antimicrobial agents used for animal therapy in pathogenic-, zoonotic- and indicator bacteria isolated from different food animals in Denmark: a baseline study for the Danish Integrated Antimicrobial Resistance Monitoring Programme (DANMAP). APMIS 106, 745–770 (1998).

    CAS  Article  Google Scholar 

  10. 10.

    European Food Safety Authority Harmonised monitoring of antimicrobial resistance in Salmonella and Campylobacter isolates from food animals in the European Union. Clin. Microbiol. Infect. 14, 522–533 (2008).

  11. 11.

    McEwan, S. A., Aarestrup, F. M. & Jordan, D. in Antimicrobial Resistance in Bacteria of Animal Origin (ed. Aarestrup, F. M.) 397–413 (ASM Press, Washington DC, 2006).

  12. 12.

    Veterinary Medicines Division European Medicines Agency, European Surveillance of Veterinary Antimicrobial Consumption, 2016 (EMA, 2016).

  13. 13.

    European Centre for Disease Prevention and Control, European Food Safety Authority & European Medicines Agency ECDC/EFSA/EMA first joint report on the integrated analysis of the consumption of antimicrobial agents and occurrence of antimicrobial resistance in bacteria from humans and food-producing animals. EFSA J. 13, 4006 (2015).

  14. 14.

    European Food Safety Authority Technical specifications on the harmonised monitoring and reporting of antimicrobial resistance in Salmonella, Campylobacter and indicator Escherichia coli and Enterococcus spp. bacteria transmitted through food. EFSA J. 10, 64 (2012).

  15. 15.

    Nordahl Petersen, T. et al. Meta-genomic analysis of toilet waste from long distance flights; a step towards global surveillance of infectious diseases and antimicrobial resistance. Sci. Rep. 5, 11444 (2015).

    Article  Google Scholar 

  16. 16.

    Xiao, L. et al. A reference gene catalogue of the pig gut microbiome. Nat. Microbiol. 1, 16161 (2016).

    CAS  Article  Google Scholar 

  17. 17.

    Munk, P. et al. A sampling and metagenomic sequencing-based methodology for monitoring antimicrobial resistance in swine herds. J. Antimicrob. Chemother. 72, 385–392 (2016).

    Article  Google Scholar 

  18. 18.

    Hasman, H. et al. Detection of mcr-1 encoding plasmid-mediated colistin-resistant Escherichia coli isolates from human bloodstream infection and imported chicken meat, Denmark 2015. Euro Suveill. 20, 30085 (2015).

    Article  Google Scholar 

  19. 19.

    Wang, Y. et al. A novel gene, optrA, that confers transferable resistance to oxazolidinones and phenicols and its presence in Enterococcus faecalis and Enterococcus faecium of human and animal origin. J. Antimicrob. Chemother. 70, 2182–2190 (2015).

    CAS  Article  Google Scholar 

  20. 20.

    Forsberg, K. J. et al. Bacterial phylogeny structures soil resistomes across habitats. Nature 509, 612–616 (2014).

    CAS  Article  Google Scholar 

  21. 21.

    Pehrsson, E. C. et al. Interconnected microbiomes and resistomes in low-income human habitats. Nature 533, 212–216 (2016).

    CAS  Article  Google Scholar 

  22. 22.

    Martínez, J. L., Coque, T. M. & Baquero, F. What is a resistance gene? Ranking risk in resistomes. Nat. Rev. Microbiol. 13, 116–123 (2014).

    Article  Google Scholar 

  23. 23.

    Knudsen, B. E. et al. Impact of sample type and DNA isolation procedure on genomic inference of microbiome composition. mSystems 1, e00095-16 (2016).

    Article  Google Scholar 

  24. 24.

    Bowers, R. M. et al. Impact of library preparation protocols and template quantity on the metagenomic reconstruction of a mock microbial community. BMC Genomics 16, 856 (2015).

    Article  Google Scholar 

  25. 25.

    Hammerum, A. M. et al. Characterization of extended-spectrum β-lactamase (ESBL)-producing Escherichia coli obtained from Danish pigs, pig farmers and their families from farms with high or no consumption of third- or fourth-generation cephalosporins. J. Antimicrob. Chemother. 69, 2650–2657 (2014).

    CAS  Article  Google Scholar 

  26. 26.

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

    CAS  Article  Google Scholar 

  27. 27.

    Anantharaman, K. et al. Thousands of microbial genomes shed light on interconnected biogeochemical processes in an aquifer system. Nat. Commun. 7, 13219 (2016).

    CAS  Article  Google Scholar 

  28. 28.

    Ma, L. et al. Metagenomic assembly reveals hosts of antibiotic resistance genes and the shared resistome in pig, chicken, and human feces. Environ. Sci. Technol. 50, 420–427 (2016).

    CAS  Article  Google Scholar 

  29. 29.

    BBduk v39.92 (Bushnell, B., 2018); https://sourceforge.net/projects/bbmap/

  30. 30.

    Li, H. & Durbin, R. Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

    CAS  Article  Google Scholar 

  31. 31.

    Zankari, E. et al. Identification of acquired antimicrobial resistance genes. J. Antimicrob. Chemother. 67, 2640–2644 (2012).

    CAS  Article  Google Scholar 

  32. 32.

    Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat. Protoc. 7, 562–578 (2012).

    CAS  Article  Google Scholar 

  33. 33.

    Fu, L., Niu, B., Zhu, Z., Wu, S. & Li, W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28, 3150–3152 (2012).

    CAS  Article  Google Scholar 

  34. 34.

    Pehrsson, E. C., Forsberg, K. J., Gibson, M. K., Ahmadi, S. & Dantas, G. Novel resistance functions uncovered using functional metagenomic investigations of resistance reservoirs. Front. Microbiol. 4, 145 (2013).

    Article  Google Scholar 

  35. 35.

    Moore, A. M. et al. Pediatric fecal microbiota harbor diverse and novel antibiotic resistance genes. PLoS ONE 8, e78822 (2013).

    Article  Google Scholar 

  36. 36.

    Sommer, M. O. A., Dantas, G. & Church, G. M. Functional characterization of the antibiotic resistance reservoir in the human microflora. Science 325, 1128–1131 (2009).

    CAS  Article  Google Scholar 

  37. 37.

    Legendre, P. & Gallagher, E. D. Ecologically meaningful transformations for ordination of species data. Oecologia 129, 271–280 (2001).

    Article  Google Scholar 

  38. 38.

    Timmerman, T. et al. Quantification and evaluation of antimicrobial drug use in group treatments for fattening pigs in Belgium. Prev. Vet. Med. 74, 251–263 (2006).

    Article  Google Scholar 

  39. 39.

    Oksanen, J. et al. vegan: Community Ecology Package v2.4-1 (CRAN, 2016); https://CRAN.R-project.org/package=vegan

  40. 40.

    Pielou, E. C. The measurement of diversity in different types of biological collections. J. Theor. Biol. 13, 131–144 (1966).

    Article  Google Scholar 

  41. 41.

    Paradis, E., Claude, J. & Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289–290 (2004).

    CAS  Article  Google Scholar 

  42. 42.

    Letunic, I. & Bork, P. Interactive Tree Of Life (iTOL): an online tool for phylogenetic tree display and annotation. Bioinformatics 23, 127–128 (2007).

    CAS  Article  Google Scholar 

  43. 43.

    Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, New York, NY, 2009).

  44. 44.

    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Article  Google Scholar 

  45. 45.

    Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol. 15, 550 (2014).

    Article  Google Scholar 

  46. 46.

    McMurdie, P. J. & Holmes, S. Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput. Biol. 10, e1003531 (2014).

    Article  Google Scholar 

  47. 47.

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

    Google Scholar 

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Acknowledgements

We thank all of the anonymous pig and poultry herd owners who agreed to participate in the study and especially everyone involved in sampling and laboratory work: M. Schlepers (Belgium); T. Ivanova, N. Cholakov, E. Gurova-Mehmedova and K. Penchev (Bulgaria); F. Nienhaus (Germany); C. L. Nielsen, P. Ryt-Hansen, B. Hølstad, B. Rasmussen and K. Nielsen (Denmark); C. Jenna, D. Virginie, E. Florent, E. Eric, S. Le Bouquin, L. Denis and T. Rodolphe (France); M. Gherpelli, M. Pegoraro and V. Carfora (Italy); D. de Vries (the Netherlands); B. Gawlik, D. Krasucka and A. Hoszowski (Poland). The EFFORT project (www.effort-against-amr.eu) and the work presented here is supported by the European Union, FP7-KBBE-2013-7, grant agreement 613754.

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F.M.A., D.H., J.A.W., T.H., D.M. and the EFFORT group designed the study. F.M.A. and B.E.K. detailed the sampling and sequencing. A.S.R.D. and the EFFORT group carried out the sampling. B.E.K. and S.J.P. conducted the DNA purification and, with P.M., organized the sequencing. R.B.H., O.Lund. and T.N.P. created the read-mapping pipeline. E.R. created the FRD. P.M., O.Lukjacenko., R.E.C.L., L.V.G., L.A.M.S., H.S., A.B., A.D.G. and H.V. carried out the bioinformatics and statistical analysis. P.M. created the figures and drafted the manuscript. All authors helped review, edit and complete the manuscript.

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Correspondence to Frank M. Aarestrup.

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Munk, P., Knudsen, B.E., Lukjancenko, O. et al. Abundance and diversity of the faecal resistome in slaughter pigs and broilers in nine European countries. Nat Microbiol 3, 898–908 (2018). https://doi.org/10.1038/s41564-018-0192-9

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