The rates and routes of transmission of multidrug resistant Klebsiella clones and genes into the clinic from environmental sources (SpARK)





The rise of antimicrobial resistance is a pressing public health crisis on a global scale, but the use of antibiotics in humans only represents a small part of the problem.

Completed project

Effective management strategies need to incorporate antibiotics in agriculture, as well as the release of these drugs, and resistant bacteria, into the environment. This project conforms to this “One-Health” framework by discovering how frequently antibiotic resistant bacteria move between humans, animals and different settings in the environment such as river water and soil.

The project focusses on a group of bacterial species called Klebsiella which are common in the environment and in animals, but also cause infections in humans and livestock that are resistant to antibiotics. One species in particular, Klebsiella pneumoniae, is a very common cause of resistant infections in hospitals and is recognised by the WHO as critically high priority. Northern Italy is a ‘hotspot’ for these infections, but it is not clear whether these bacteria are confined to hospitals, or are also present elsewhere.

To address this, we took 3500 Klebsiella strains from hospital patients, wild and domesticated animals and multiple environmental sources. Importantly, all the strains were taken from a single city, Pavia, in Lombardy. By sequencing the genomes of these bacteria, combined with mathematical modelling, we could tell which resistant genes were present, and how the strains were moving. We found that resistant genes are strains were uncommon outside of hospitals, and that the vast majority (around 75%) of Klebsiella in humans comes from other humans. However, we did find some risk of transmission from companion animals (dogs and cats) and water sources.

Project partners

  • Edward Feil, University of Bath, United Kingdom (Coordinator)
  • Piero Marone, Fondazione IRCCS Policlinico San Matteo, Italy
  • Sylvain Brisse, Pasteur Institute, France
  • Louise Matthews, University of Glasgow, United Kingdom
  • Jukka Corander, University of Oslo, Norway
  • David Aanensen, Big Data Institute, Oxford, United Kingdom
  • Alan McNally, University of Birmingham, United Kingdom

Project resources