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Achieving Optimal Growth through Product Feedback Inhibition in Metabolism
Author(s) -
Sidhartha Goyal,
Jie Yuan,
Tai C. Chen,
Joshua D. Rabinowitz,
Ned S. Wingreen
Publication year - 2010
Publication title -
plos computational biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.628
H-Index - 182
eISSN - 1553-7358
pISSN - 1553-734X
DOI - 10.1371/journal.pcbi.1000802
Subject(s) - metabolite , negative feedback , feedback control , metabolic pathway , product inhibition , systems biology , nutrient , positive feedback , metabolism , metabolomics , biological system , computer science , biochemical engineering , biology , biochemistry , enzyme , computational biology , bioinformatics , ecology , physics , engineering , control engineering , non competitive inhibition , electrical engineering , quantum mechanics , voltage
Recent evidence suggests that the metabolism of some organisms, such as Escherichia coli , is remarkably efficient, producing close to the maximum amount of biomass per unit of nutrient consumed. This observation raises the question of what regulatory mechanisms enable such efficiency. Here, we propose that simple product-feedback inhibition by itself is capable of leading to such optimality. We analyze several representative metabolic modules—starting from a linear pathway and advancing to a bidirectional pathway and metabolic cycle, and finally to integration of two different nutrient inputs. In each case, our mathematical analysis shows that product-feedback inhibition is not only homeostatic but also, with appropriate feedback connections, can minimize futile cycling and optimize fluxes. However, the effectiveness of simple product-feedback inhibition comes at the cost of high levels of some metabolite pools, potentially associated with toxicity and osmotic imbalance. These large metabolite pool sizes can be restricted if feedback inhibition is ultrasensitive. Indeed, the multi-layer regulation of metabolism by control of enzyme expression, enzyme covalent modification, and allostery is expected to result in such ultrasensitive feedbacks. To experimentally test whether the qualitative predictions from our analysis of feedback inhibition apply to metabolic modules beyond linear pathways, we examine the case of nitrogen assimilation in E. coli , which involves both nutrient integration and a metabolic cycle. We find that the feedback regulation scheme suggested by our mathematical analysis closely aligns with the actual regulation of the network and is sufficient to explain much of the dynamical behavior of relevant metabolite pool sizes in nutrient-switching experiments.

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