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

Objective

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.

Investigators
Bono, James; Gally, Da, La.; Fitzgerald, St, .
Institution
USDA - Agricultural Research Service
Start date
2021
End date
2023
Project number
NEBW-2020-03319
Accession number
1024223
Categories