Li Chunhe, Wang Erkang, Wang Jin
State Key Laboratory of Electroanalytical Chemistry, Changchun Institute of Applied Chemistry, Chinese Academy of Sciences, Changchun, Jilin 130022, P.R. China.
ACS Synth Biol. 2012 Jun 15;1(6):229-39. doi: 10.1021/sb300020f. Epub 2012 May 11.
Metabolic networks have gained broad attention in recent years as a result of their important roles in biological systems. However, how to quantify the global stability of the metabolic networks is still challenging. We develop a probabilistic landscape approach to investigate the global natures of the metabolic system under external fluctuations. As an example, we choose a model of the carbohydrate metabolism and the anaplerotic synthesis of oxalacetate in Aspergillus niger under conditions of citric acid accumulation to explore landscape topography. The landscape has a funnel shape, which guarantees the robustness of system under fluctuations and perturbations. Robustness ratio (RR), defined as the ratio of gap between lowest potential and average potential versus roughness measured by the dispersion or square root of variations of potentials, can be used to quantitatively evaluate the global stability of metabolic networks, and the larger the RR value, the more stable the system. Results of the entropy production rate imply that nature might evolve such that the network is robust against perturbations from environment or network wirings and performs specific biological functions with less dissipation cost. We also carried out a sensitivity analysis of parameters and uncovered some key network structure factors such as kinetic rates or wirings connecting the protein species nodes, which influence the global natures of the system. We found there is a strong correlation between the landscape topography and the input-output response. The more stable and robust the metabolic network is, the sharper the response is.
近年来，代谢网络因其在生物系统中的重要作用而受到广泛关注。然而，如何量化代谢网络的全局稳定性仍然具有挑战性。我们开发了一种概率景观方法来研究外部波动下代谢系统的全局性质。作为一个例子，我们选择了黑曲霉在柠檬酸积累条件下的碳水化合物代谢和草酰乙酸的回补合成模型，以探索景观地形。该景观具有漏斗形状，这保证了系统在波动和扰动下的稳健性。稳健比（RR）定义为最低势与平均势之间的差距与由势的离散度或平方根测量的粗糙度之比，可用于定量评估代谢网络的全局稳定性，RR值越大，系统越稳定。熵产生率的结果表明，自然可能会这样进化，使得网络对来自环境或网络布线的扰动具有稳健性，并以较低的耗散成本执行特定的生物学功能。我们还进行了参数敏感性分析，发现了一些关键的网络结构因素，如连接蛋白质物种节点的动力学速率或布线，它们影响系统的全局性质。我们发现景观地形与输入-输出响应之间存在很强的相关性。代谢网络越稳定和稳健，响应就越尖锐。
