title: Simulating Serial-Target Antibacterial Drug Synergies Using Flux Balance Analysis.
abstract: Flux balance analysis (FBA) is an increasingly useful approach for modeling the behavior of metabolic systems. However, standard FBA modeling of genetic knockouts cannot predict drug combination synergies observed between serial metabolic targets, even though such synergies give rise to some of the most widely used antibiotic treatments. Here we extend FBA modeling to simulate responses to chemical inhibitors at varying concentrations, by diverting enzymatic flux to a waste reaction. This flux diversion yields very similar qualitative predictions to prior methods for single target activity. However, we find very different predictions for combinations, where flux diversion, which mimics the kinetics of competitive metabolic inhibitors, can explain serial target synergies between metabolic enzyme inhibitors that we confirmed in Escherichia coli cultures. FBA flux diversion opens the possibility for more accurate genome-scale predictions of drug synergies, which can be used to suggest treatments for infections and other diseases.
authors.affiliation: Boston University, 44 Cummington St, Boston, MA, United States of America.
authors.forename: Andrew S
authors.initials: AS
authors.lastname: Krueger
authors.affiliation: Technical University of Denmark, Novo Nordisk Foundation Center for Biosustainability, Hørsholm, Denmark.
authors.forename: Christian
authors.initials: C
authors.lastname: Munck
authors.affiliation: Center for Genome Science & Systems Biology, Washington University School of Medicine, St Louis, Missouri, United States of America.|Department of Pathology & Immunology, Washington University School of Medicine, St Louis, Missouri, United States of America.|Department of Biomedical Engineering, Washington University, St. Louis, Missouri, United States of America.
authors.forename: Gautam
authors.initials: G
authors.lastname: Dantas
authors.affiliation: Department of Genetics, Harvard Medical School, Boston, Massachusetts, United States of America.
authors.forename: George M
authors.initials: GM
authors.lastname: Church
authors.affiliation: Boston University, 44 Cummington St, Boston, MA, United States of America.|Broad Institute, Cambridge Center, Cambridge, Massachusetts, United States of America.
authors.forename: James
authors.initials: J
authors.lastname: Galagan
authors.affiliation: Boston University, 44 Cummington St, Boston, MA, United States of America.
authors.forename: Joseph
authors.initials: J
authors.lastname: Lehár
authors.affiliation: Technical University of Denmark, Novo Nordisk Foundation Center for Biosustainability, Hørsholm, Denmark.
authors.forename: Morten O A
authors.initials: MO
authors.lastname: Sommer
mesh_terms: D000900:Anti-Bacterial Agents / Q000494:pharmacology*; D004357:Drug Synergism; D004843:Epistasis, Genetic; D004926:Escherichia coli / Q000187:drug effects / Q000378:metabolism*; D005798:Genes, Bacterial; D020128:Inhibitory Concentration 50; D060847:Metabolic Engineering; D064688:Metabolic Flux Analysis; D053858:Metabolic Networks and Pathways; D008826:Microbial Sensitivity Tests; D050296:Microbial Viability
chemical_list: D000900:Anti-Bacterial Agents
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