MicrobeModel: Modelling the water and fish microbiomes to monitor and predict pathogen outbreaks

By fostering high stock densities fish farming practices reduce water quality and increase host stress, thus favoring disease spread. For these reasons, bacterial infectious diseases are one of the major challenges faced by the aquaculture industry. Commensal bacteria, i.e. the microbiome, play an important role in controlling pathogenic elements through interspecific competition, hence microbiome diversity and the host health are positively related. Recently, a statistical tool (BioMico) has been developed to model and predict microbiomes given a set of independent variables. In this project we aim to apply BioMiCo, to model and predict the skin microbiomes of two farmed species as well as the water microbiome in natural and farming environments. This will allow predicting disease outbreaks and identify which combination of variables favour pathogens. The outcomes of this project will allow improving the management of diseases in farms and also in estuarine ecosystems.