Abstract Constraint-based models such as flux balance analysis (FBA) are a powerful tool to study biological metabolic networks. Under the hypothesis that cells operate at an optimal growth rate as the result of evolution and natural selection, this model successfully predicts most cellular behaviours in growth rate. However, the model ignores the fact that cells can change their cellular metabolic states during evolution, leaving optimal metabolic states unstable. Here, we consider all the cellular processes that change metabolic states into a single term `noise', and assume that cells change metabolic states by randomly walking in feasible solution space. By simulating a state of a cell randomly walking in the constrained solution space of metabolic networks, we found that in a noisy environment cells in optimal states tend to travel away from these points. On considering the competition between the noise effect and the growth effect in cell evolution, we found that there exists a trade-off between these two effects. As a result, the population of the cells contains different cellular metabolic states, and the population growth rate is at suboptimal states.
Received: 25 June 2009
Revised: 24 August 2009
Accepted manuscript online:
Fund: Project supported by the National
Natural Science Foundation of China (Grant No 10721403), the MOST of
China (Grant No 2009CB918500), and the National Basic Research
Program of China (Grant Nos 2006CB910706 and 2007CB814800).
Cite this article:
Li Zheng-Yan(李政言),Xie Zheng-Wei(谢正伟), Chen Tong(陈同), and Ouyang Qi(欧阳颀) Noise effect in metabolic networks 2009 Chin. Phys. B 18 5544
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