Using Galleria mellonella to study pathogen dissemination and anti-infective surface coatings.

Abstract

Hospital associated infections and localised hospital outbreaks are a major challenge for infection control teams (ICTs) in hospitals around the world. Advances in artificial intelligence and infection modelling have enabled ICT teams to better predict and trace infection spread. However, it is notoriously difficult to replicate bacterial dissemination or validate prediction models in a laboratory setting due to a lack of effective in vivo models. In this work, we sought to develop Galleria mellonella as a model organism to replicate the dissemination of pathogens in a hospital intensive care unit (ICU). By combining this model organism with 3D printed models of a real hospital ICU, we are able to demonstrate that larvae do disseminate the multidrug resistant pathogen Acinetobacter baumannii within this ICU model and that it is possible to use this model to identify infection hotspots. Importantly, this model can also be used for intervention strategy testing as we also show that bacterial dissemination can be significantly mitigated by the introduction of antimicrobial wall surface coatings. This model provides a robust platform for the testing of antimicrobial surface coatings as well as the study of genetic determinants with a role in pathogen dissemination.