Support vector machine applied to predict the zoonotic potential of E. coli O157 cattle isolates.

ABSTRACT: Sequence analyses of pathogen genomes facilitate the tracking of disease outbreaks and allow relationships between strains to be reconstructed and virulence factors to be identified. However, these methods are generally used after an outbreak has happened. Here, we show that support vector machine analysis of bovine E. coli O157 isolate sequences can be applied to predict their zoonotic potential, identifying cattle strains more likely to be a serious threat to human health. Notably, only a minor subset (less than 10%) of bovine E. coli O157 isolates analyzed in our datasets were predicted to have the potential to cause human disease; this is despite the fact that the majority are within previously defined pathogenic lineages I or I/II and encode key virulence factors. The predictive capac

SUBMITTER: Lupolova N 

PROVIDER: S-EPMC5056084 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature