Evaluating Proteome Allocation of Saccharomyces cerevisiae Phenotypes with Resource Balance Analysis

Themes: Conversion

Keywords: Modeling



(a) Schematic representation of the scRBA model (macro)molecular participants and reactions. (b) Overview of bisection method and the RBA linear programming (RBA-LP) formulation that are solved iteratively to obtain the maximal growth rate. Flux variables are highlighted in red and the growth rate variable is highlighted in green. The topology of all scRBA model captured variables are shown in Fig. 1a. Model parameters are briefly explained in the text and formulation details are available in the Supplementary Text 1.

Saccharomyces cerevisiae is an important model organism and a workhorse in bioproduction. Here, we reconstructed a compact and tractable genome-scale resource balance analysis (RBA) model (i.e., named scRBA) to analyze metabolic fluxes and proteome allocation in a computationally efficient manner. Resource capacity models such as scRBA provide the quantitative means to identify bottlenecks in biosynthetic pathways due to enzyme, compartment size, and/or ribosome availability limitations. ATP maintenance rate and in vivo apparent turnover numbers (kapp) were regressed from metabolic flux and protein concentration data to capture observed physiological growth yield and proteome efficiency and allocation, respectively. Estimated parameter values were found to vary with oxygen and nutrient availability. Overall, this work (i) provides condition-specific model parameters to recapitulate phenotypes corresponding to different extracellular environments, (ii) alludes to the enhancing effect of substrate channeling and post-translational activation on in vivo enzyme efficiency in glycolysis and electron transport chain, and (iii) reveals that the Crabtree effect is underpinned by specific limitations in mitochondrial proteome capacity and secondarily ribosome availability rather than overall proteome capacity.


GitHub Repository (includes code, model data, parameterization, and validation)

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