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

Abstract

Cocktail combinations of bacteria-infecting viruses (bacteriophage), 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 phage 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: 1) we found that treatment with two E. coli phage led to the evolution of a mucoid phenotype that provided cross-resistance against both phage, and 2) S. enterica set the growth rate of the co-culture, 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. Originality-Significance StatementCross-feeding, or exchanging nutrients among bacteria, is a type of ecological interaction found in many important microbial communities. Furthermore, cross-feeding interactions are found to play a role in some infections, and research into treating infections with combinations of bacteriophage in cocktails is growing. Here, we used a combination of mathematical modelling and wet-lab experiments to optimize suppression of a model pathogen with a bacteriophage cocktail in a synthetic cross-feeding bacterial coculture. A key finding was that a physiological parameter - growth rate - of the bacteria was important to consider when choosing the most effective cocktail formulation. This work is novel because it highlights an unexpected multispecies-targeting strategy for designing phage cocktails for cross-feeding pathogens and has relevance to many ecological systems ranging from human health to agriculture. We demonstrate how leveraging knowledge of a pathogens ecological interaction has the potential to improve precision medicine and management of microbial systems.