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Genome-scale models (GEMs) have been expanded to compute both the metabolic and proteomic states of a cell in different conditions. These multiscale models called GEMs of metabolism and macromolecular expression (ME-models) expand the scope of GEMs and provide greater predictive abilities and therefore are being increasingly used in system understanding of microbial biology. In this review, we describe ME-models, their advantages, and computational advances. We then describe extensions of ME-models to model stress response and a related human red blood cell model that integrates metabolism and macromolecular mechanisms. Finally, we discuss how ME-models were recently used to explain resource allocation trade-offs for microbial growth in adaptively evolved strains, in synthetic communities, and under stress.
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Dahal et al. (2021) studied this question.
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