Abstract
Cellular functions are shaped by reaction networks whose dynamics are determined by the concentrations of underlying components. However, cellular mechanisms ensuring that a component's concentration resides in a given range remain elusive. We present network properties which suffice to identify components whose concentration ranges can be efficiently computed in mass-action metabolic networks. We show that the derived ranges are in excellent agreement with simulations from a detailed kinetic metabolic model of Escherichia coli. We demonstrate that the approach can be used with genome-scale metabolic models to arrive at predictions concordant with measurements from Escherichia coli under different growth scenarios. By application to 14 genome-scale metabolic models from diverse species, our approach specifies the cellular determinants of concentration ranges that can be effectively employed to make predictions for a variety of biotechnological and medical applications.
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CITATION STYLE
Küken, A., Eloundou-Mbebi, J. M. O., Basler, G., & Nikoloski, Z. (2019). Cellular determinants of metabolite concentration ranges. PLoS Computational Biology, 15(1). https://doi.org/10.1371/journal.pcbi.1006687
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