Journal
PLOS COMPUTATIONAL BIOLOGY
Volume 15, Issue 1, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1006687
Keywords
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Funding
- Max Planck Society
- German Research Foundation [NI 1472/4-2, NI 1472/4-1]
- Federal Ministry of Education and Research of Germany within project RECONSTRUCT [031B0200 A-E]
- Federal Ministry of Education and Research of Germany within project FULLTHROTTLE [031B0205 B]
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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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