Global monitoring of antimicrobial resistance based on metagenomics analyses of urban sewage

Rene S Hendriksen, Patrick Munk, Patrick Njage, Bram van Bunnik, Luke McNally, Oksana Lukjancenko, Timo Röder, David Nieuwenhuijse, Susanne Karlsmose Pedersen, Jette Kjeldgaard, Rolf S Kaas, Philip Thomas Lanken Conradsen Clausen, Josef Korbinian Vogt, Pimlapas Leekitcharoenphon, Milou G M van de Schans, Tina Zuidema, Ana Maria de Roda Husman, Simon Rasmussen, Bent Petersen, Global Sewage Surveillance project consortiumClara Amid, Guy Cochrane, Thomas Sicheritz-Ponten, Heike Schmitt, Jorge Raul Matheu Alvarez, Awa Aidara-Kane, Sünje J Pamp, Ole Lund, Tine Hald, Mark Woolhouse, Marion P Koopmans, Håkan Vigre, Thomas Nordahl Petersen, Frank M Aarestrup

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Antimicrobial resistance (AMR) is a serious threat to global public health, but obtaining representative data on AMR for healthy human populations is difficult. Here, we use metagenomic analysis of untreated sewage to characterize the bacterial resistome from 79 sites in 60 countries. We find systematic differences in abundance and diversity of AMR genes between Europe/North-America/Oceania and Africa/Asia/South-America. Antimicrobial use data and bacterial taxonomy only explains a minor part of the AMR variation that we observe. We find no evidence for cross-selection between antimicrobial classes, or for effect of air travel between sites. However, AMR gene abundance strongly correlates with socio-economic, health and environmental factors, which we use to predict AMR gene abundances in all countries in the world. Our findings suggest that global AMR gene diversity and abundance vary by region, and that improving sanitation and health could potentially limit the global burden of AMR. We propose metagenomic analysis of sewage as an ethically acceptable and economically feasible approach for continuous global surveillance and prediction of AMR.

Original languageEnglish
Article number1124
Number of pages12
JournalNature Communications
Publication statusPublished - 8 Mar 2019

Keywords / Materials (for Non-textual outputs)

  • global surveillance
  • antimicrobial resistance
  • AMR
  • wastewater
  • sewage
  • metagenomics
  • resistome
  • machine learning
  • prediction


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