PRECISION BACTERIOPHAGE IDENTIFICATION THROUGH MACHINE LEARNING FOR MITIGATING PERSISTENT COLONIZATION OF SHIGA TOXIN-PRODUCING ESCHERICHIA COLI O157:H7 IN CATTLE

The goal of this proposal is to demonstrate the utility of bacteriophage cocktails to reduce or eliminate the shedding of STEC O157:H7 in cattle feces and to develop a bioinformatical approach to predict sensitivity of STEC O157:H7 strains to bacteriophage cocktails.Objectives: To conduct interaction assays between E. coli O157:H7 strains, and phages known to be active against E. coli O157:H7 to determine interactions of selecting phages from different activity groups to use in phage cocktails. To build a machine learning classifier to allow phage cocktails to be developed based only on the sequence of an E. coli O157:H7 isolate without repeating the interaction assays. To validate the tailored phage cocktail through a cattle challenge study by administering the cocktail rectally (at the known site of colonization) to cattle inoculated with a STEC O157:H7 strain known to persistently colonize cattle.