Background
Carbapenemase-producing Enterobacterales (CPE) are an important cause of hospital-acquired infections, with high mortality rates.
Methods
Four studies were conducted across Thailand and the UK to investigate whether bacterial genomic data combined with clinical information can provide high-resolution data on CPE genomic epidemiology, mechanisms of colistin resistance, and to demonstrate the robustness of such approach for CPE outbreak investigations.
Results
Carbapenem-resistant K. pneumoniae was the most prevalent CPE isolate found to colonise patients and cause infection at Siriraj Hospital, Bangkok. The most important risk factor associated with subsequent CPE infection was wound colonisation with CPE. Phylogenetic analysis revealed the polyclonal spread of carbapenemase-producing K. pneumoniae with two major subclades identified: ST16 and ST231. The follow-on study investigating urban hospitalised patients, rural farmers and swine did not reveal any potential transmissions of bacterial strains or plasmid-mediated colistin resistance genes between humans and swine. The CPE outbreak study from London revealed diverse species (predominantly Enterobacter spp.), of which 86% harboured an IncHI2 plasmid carrying carbapenamase-encoding gene (blaIMP). Phylogenetic analysis of IncHI2 plasmids identified 12 clusters which showed significant association with patient contact and movements, which had been missed on initial investigations.
Conclusion
The genomic epidemiology of CPE in combination with clinical information can be used to guide empirical antibiotic treatment and improve management strategies for CPE infections, such as targeting the prevention of wound infections in hospitalised patients and their management. The study from London involving the integration of patient information such as patient network models with detailed genomic analysis revealed a previously unidentified transmission chain and provided a high-resolution view of the spread of emerging resistance genes via plasmids among different bacterial species. This approach can be applied to outbreak investigations and may be adapted to track the spread of bacteria within hospital networks in a wide range of scenarios.