{"doi":"10.1101/2020.06.08.140301","title":"Phage cocktail strategies for the suppression of a pathogen in a cross-feeding coculture","abstract":"Summary 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 Statement Cross-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 pathogen’s ecological interaction has the potential to improve precision medicine and management of microbial systems.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2020,"id":126862,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9578,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":575364,"name":"Jeremy Anisman","orcid":null,"position":1,"is_corresponding":false},{"id":315180,"name":"Jeremy M. Chacón","orcid":"0000-0002-6129-2604","position":2,"is_corresponding":false},{"id":315181,"name":"William R. Harcombe","orcid":"0000-0001-8445-2052","position":3,"is_corresponding":false},{"id":574857,"name":"Lisa Fazzino","orcid":"0000-0002-3793-6916","position":0,"is_corresponding":true}],"reference_count":57,"raw_metadata":null,"created_at":"2026-07-18T23:15:27.226519Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}