(23b) Evaluating Proteome Allocation of Saccharomyces Cerevisiae Phenotypes with Resource Balance Analysis

Saccharomyces cerevisiae is an important model organism and a workhorse in biochemical production. Using available molecular biology information and proteomics data we reconstructed and parameterized a genome-scale resource balance analysis (RBA) model (i.e., scRBA) that captures both cellular metabolism and proteome allocation. Specifically, scRBA contains the genome-scale metabolic network plus production pathways for protein, enzyme, and ribosome. The RBA system is constrained by reaction‑enzyme and protein‑ribosome coupling equations, and by experimentally observed rRNA and protein capacity. ATP maintenance rates and in vivo apparent turnover numbers (k_app) parameters were regressed from metabolic flux and protein concentration data. Our k_app parameterization workflow accounts for enzyme subunit stoichiometry and estimates minimally required intracellular fluxes that satisfy observed extracellular fluxes. Estimated parameters were found to differ when perturbing oxygen and nutrient availability. k_app values are higher in vivo compared to in vitro reported values for some enzymes in glycolysis, electron transport chain, and amino acyl‑tRNA synthetase pathways reflecting their higher in vivo efficiency, matching literature‑reported metabolons and post-translational modifications. We benchmark scRBA by recapitulating yeast’s aerobic fermentation phenotypes (i.e., the Crabtree effect) and proteome allocation, as well as demonstrate its applicability by predicting necessary proteome re-allocation from wild-type allocation to achieve optimal product yield.