During 2017 and 2018 our lab, in collaboration with local hospitals and the Melbourne Genomics Health Alliance (funded by the State Government of Victoria, Department of Health and Human Services, and the ten member organisations), undertook the “Controlling Superbugs” flagship study with the aim of assessing whether genomic sequencing could track the transmission of antibiotic resistant bacteria in real-time across multiple hospitals.
The project focussed on four problem pathogens: methicillin resistant Staphylococcus aureus (MRSA), vancomycin resistant Enterococcus faecium (VRE), ESBL Escherichia coli (ESBL-Ec) and Klebsiella pneumoniae (ESBL-Kp). Identifying transmission and spread of these pathogens within the hospital environment early would help guide targeted interventions and ultimately reduce the number of patients that become infected.
Using computer programs fluent in the language of the genetic code we can compare the bacterial genomes and calculate the number of differences between them. Then, if the genomes of two bacteria are shown to be very similar to each other, we can infer that a transmission event has occurred and intervene to stop further spread.
The project was a success, using genomics to identify numerous likely transmission events that were strongly supported by epidemiological evidence (the resulting papers are available here and here). However, our team felt that there was room for improvement and wanted to further refine our methods, particularly in relation to the stability of the results as new samples were added.
We focused on VRE as it was sometimes difficult to analyse using our original genomics pipeline due to factors including the extensive diversity of the species. We wanted to develop a methodology that could be used to produce reliable and replicable transmission inferences, regardless of the number or diversity of the isolates included in the analysis.
To address this, using the data collected as part of the “Controlling Superbugs” project, we systematically tested several different genomic approaches to transmission identification, considering aspects such as accuracy, scalability, stability and more. We have now developed a standardised genomic framework for inferring VRE transmission that could be the basis for global deployment of VRE genomics into routine outbreak detection and investigation. It uses core genome multilocus sequence type clustering (cgMLST) followed by pairwise comparison using split k-mer analysis (SKA). The proposed pipeline is outlined in the figure below.
Our methodological framework fulfills four key criteria for widespread implementation of a genomic pipeline; (i) stable over time as additional isolates are added to the analysis; (ii) standardised to allow for comparison across sites or hospitals; (iii) computationally efficient; and (iv) allows for automation and require minimal intervention and interpretation.
We hope that the method will be widely adopted by sequencing laboratories servicing hospitals, making it easier to rapidly screen for and identify probable transmission of antibiotic-resistant bacteria, and to standardise and compare between transmissions between hospital sites. This method is also applicable to other problem nosocomial bacteria due to its ability to cope with highly diverse and highly clonal bacterial isolates.