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Phage cocktail strategies for the suppression of a pathogen in a cross-feeding coculture.


ABSTRACT: Cocktail combinations of bacteria-infecting viruses (bacteriophages) can suppress pathogenic bacterial growth. However, predicting how phage cocktails influence microbial communities with complex ecological interactions, specifically cross-feeding interactions in which bacteria exchange nutrients, remains challenging. Here, we used experiments and mathematical simulations to determine how to best suppress a model pathogen, E. coli, when obligately cross-feeding with S. enterica. We tested whether the duration of pathogen suppression caused by a two-lytic phage cocktail was maximized when both phages targeted E. coli, or when one phage targeted E. coli and the other its cross-feeding partner, S. enterica. Experimentally, we observed that cocktails targeting both cross-feeders suppressed E. coli growth longer than cocktails targeting only E. coli. Two non-mutually exclusive mechanisms could explain these results: (i) we found that treatment with two E. coli phage led to the evolution of a mucoid phenotype that provided cross-resistance against both phages, and (ii) S. enterica set the growth rate of the coculture, and therefore, targeting S. enterica had a stronger effect on pathogen suppression. Simulations suggested that cross-resistance and the relative growth rates of cross-feeders modulated the duration of E. coli suppression. More broadly, we describe a novel bacteriophage cocktail strategy for pathogens that cross-feed.

SUBMITTER: Fazzino L 

PROVIDER: S-EPMC7533344 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Phage cocktail strategies for the suppression of a pathogen in a cross-feeding coculture.

Fazzino Lisa L   Anisman Jeremy J   Chacón Jeremy M JM   Harcombe William R WR  

Microbial biotechnology 20200819 6


Cocktail combinations of bacteria-infecting viruses (bacteriophages) can suppress pathogenic bacterial growth. However, predicting how phage cocktails influence microbial communities with complex ecological interactions, specifically cross-feeding interactions in which bacteria exchange nutrients, remains challenging. Here, we used experiments and mathematical simulations to determine how to best suppress a model pathogen, E. coli, when obligately cross-feeding with S. enterica. We tested whethe  ...[more]

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