In this exciting proposal the research team will tackle questions on how Enterococcus cecorum evolved from a commensal to an emergent pathogen, by performing whole genome sequencing (WGS). Bioinformatic pipelines, such as the APHA SeqFinder pipeline will help map raw reads from Illumina WGS to genes present in an updated APHA SeqFinder virulence/AMR genes database, to identify any variants present in isolates from diseased birds. Comparative genomics and circularisation of E. cecorum genomes from hybrid assemblies of short- and long-read WGS will identify virulence factors and antimicrobial resistance (AMR) genes gained been by horizontal transfer of mobile genetic elements such as plasmids, phages, transposons etc. uniquely present in isolates from diseased birds. Phylogenetic analysis will detect any lineages from diseased poultry enriched with virulence genes. These determinants will be incorporated into quantitative real-time (q)PCR assays and be the basis of rapid diagnostic pen-side tests in future. In-depth sampling will be performed by swabbing the environment on five farms that are identified to have a history of E. cecorum infection at different times in the poultry production cycle. A qPCR previously published for sensitive and specific detection of E. cecorum will be used to detect its presence in the environment. Stress studies performed on Enterococcus sp. will be adapted to determine if E. cecorum pathogens survive in hostile environments, and whether a particular variant/lineage is more successful than others. Video cameras and sensors associated with analytical behaviour software such as EyeNamic and Noldus EthoVision, that uses machine learning algorithms to translate video images into indices of behaviour, will be used for monitoring poultry houses. Quantification of behaviours over different time periods will help detect any subtle changes due to E. cecorum infection that can be verified by veterinary examinations.