Genome-scale Modeling of Metabolism and Macromolecular Expression and Their Applications

Genome-scale models (GEMs) are predictive tools to study genotype-phenotype relationships in biological systems. Initially, genome-scale models were used for predicting the metabolic state of the organism given the nutrient condition and genetic perturbation (if any). Such metabolic (M-) models have been successfully developed for diverse organisms in both prokaryotes and eukaryotes. In this review, we focus our attention to genome-scale models of metabolism and macromolecular expression or ME-models. ME-models expand the scope of M-models by incorporating macromolecular biosynthesis pathways of transcription and translation. ME-models can predict the proteome investment in metabolism under any given condition. Therefore, ME-models significantly improve the quantitative prediction of gene expression. Unlike M-models that can predict biological properties in only nutrient-limited condition, ME-models can do so in both nutrient- and proteome-limited conditions. There are a few limitations of ME-models, many of which have now been largely overcome, making them more attractive to the broader research community. We finally discuss the applications of GEMs in general, and how they have been applied for biomedical, bioengineering and bioremediation purposes.