Competing constraints on protein availability and nutrient uptake reshape yeast genetic interactions
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Epistasis predicted by enzyme-constrained metabolic models is computed at a single value of the protein available to metabolism, although that amount varies two-to three-fold with growth rate. We ask how epistatic interactions are affected by computing every single and pairwise gene deletion in an enzyme-constrained model of Saccharomyces cerevisiae while sweeping protein availability, with and without a bound on nutrient uptake. Protein availability changes relative fitness only under co-limitation, when the protein pool and a nutrient constraint limit growth together. The pool alone, the configuration in which these models are calibrated, makes protein a mere scale factor: no interaction changes sign. Under co-limitation, one genetic interaction in three is gained or lost across the physiological range. Most of this is inherited from single mutants of the respiratory machinery, which is recruited as protein becomes available. The epistasis between a glycolytic lesion with a protein-expensive bypass and the respiratory chain changes sign where the optimum switches from fermentation to respiration. We also find protein-priced interactions: the network supplies a bypass around each deletion and the pool gives it a price, so two genes with no stoichiometric coupling interact whenever the bypass around one competes with the route of the other for the protein pool. Isozyme pairs predicted neutral by flux balance analysis show negative epistasis for the same reason. Relative fitness depends on protein availability and nutrient supply only through their ratio. Thus, nutrient supply is a directly accessible experimental parameter to test epistatic interactions. Sign inversion, isozyme pairs, and interactions with cofactor-consuming branches are predictions a condition-resolved genetic interaction screen can test.
Author summary
Enzymes are protein, and a cell has only a limited amount. The share a yeast cell can spend on metabolic enzymes varies two-to three-fold between slow and fast growth. Metabolic models include this limit, yet usually hold it at one fitted value when investigating genetic interactions: whether deleting two genes together is more or less harmful than expected from the separate deletions.
We recomputed every single and double deletion while varying the protein available to the modeled yeast metabolism. Changing protein availability increased growth in mutants and wild type almost equally when protein was the only limitation and left their interactions unchanged. About one-third of interactions appeared or disappeared across the physiological range once glucose uptake also limited growth. Additionally, the model predicts that one class of interaction reverses sign when the cell shifts from fermentation to respiration. Other interactions linked genes in different pathways: when the network offers a detour around each deletion, the enzyme limit gives every detour a cost, and a detour paid with enzyme that another reaction needs makes the double deletion cost more, or less, than both singles together. This simulation-based prediction could be tested experimentally by comparing genetic interactions under controlled high and low glucose supply.
