Science AdvancesSystems BiologyPeer-reviewed journal article
Synergy and antagonism in a genome-scale model of metabolic hijacking by bacteriophage
Jordan C. RozumiD, William Sineath, Pavlo BohutskyiiD, Jordan QuennevilleiD, D. H. Kim, Connah JohnsoniD, Angad P. MehtaiD, James E. EvansiD, David D. PollockiD, Weijun QianiD, Margaret S. CheungiD, Ruonan WuiD, Song FengiD
Abstract
Bacteriophage auxiliary metabolic genes (AMGs) alter host metabolism by hijacking reactions. Previous studies used functional annotations to infer AMG impacts but neglected propagation effects on global metabolism and phage production. We demonstrate the first integration of AMGs and phage assembly into a genome-scale metabolic model, using a general method applied to the infection of Prochloroccocus marinus MED4 by P-HM2. We experimentally validate our approach to predicting AMG impact on growth using cp12 mutations in Syne-chococcus elongatus. We predict that 17 directly hijacked reactions substantially impact over 30% of the metabolism, including carbon fixation, photosynthesis, and nucleotide synthesis. We find that indirect impacts are synergistically and antagonistically coupled and are either phage-aligned--shifting feasible reaction velocities in accordance with maximal phage production--or phage-antialigned. Pareto optimization reveals that phage-aligned reactions limit host growth, while phage-antialigned reactions do not. We provide systems-level insight into AMG perturbations, highlighting how nontrivial cascading effects shape microbial functions.
- organism: bacteria (other)
- assay: whole-genome sequencing
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 5
- FWCI
- 17.34
- Field percentile
- top 1%
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