On the conditions for shifts in metabolic strategies

Many heterotrophic microorganisms gradually replace an energetically-efficient mode of metabolism by an inefficient, more wasteful overflow metabolism above a critical growth rate, even though the energy demand continues to rise with growth rate. For instance, complete respiration of a sugar is replaced by its fermentation. In this paper, we aim to acquire a comprehensive overview of the behaviour of the metabolic fluxes and coarse-grained protein expression as function of the growth rate of the cell, by integrating previously proposed mechanisms and models into one framework. We derive the conditions for a metabolic shift to happen, by using and extending an existing core model of metabolism and growth that is qualitatively in agreement with experimental data. Assuming a fixed cellular protein content, the model shows that protein expression of efficient metabolism and anabolism rises as function of growth rate until a critical value is reached. This growth-associated protein expression is at the expense of proteins associated with future adaptation. At the critical growth rate, this preparatory-protein pool is reduced to zero. Beyond the critical growth rate, the anabolic protein pool and the energy demand continue to rise and therefore less protein remains for catabolism. In this regime, the inefficient metabolism gradually takes over ATP synthesis from the efficient mode. It can do so if it requires less protein per unit of ATP flux. We show that such a metabolic shift can occur only if the maximal growth rate of the inefficient mode is higher than the critical growth rate, and that this is equivalent to the second mode having a higher proteome efficiency than the first. Finally, we reduce a genome-scale model of protein expression in the yeast Saccharomyces cerevisiae to a variant of our core model and show that it is still qualitatively in agreement with the experimental data used to validate the original model. This study provides a synthesis that integrates and unifies existing models (coarse-grained and genome-scale models), that all aim to understand shifts in metabolic strategies.