多催化剂反应在密集催化反应网络模型中引发突变转变
Multicatalyst reactions induce abrupt transition in a dense catalytic reaction network model
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- The University of Tokyo（东京大学）
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中文总结 AI 辅助
本研究将Furusawa--Kaneko模型推广至多催化剂反应，利用动力学平均场理论揭示催化剂数量影响代谢网络的分岔结构，为代谢双稳态和突变切换提供机制解释。
中文摘要 AI 辅助
我们将Furusawa--Kaneko模型（一种细胞内催化反应网络的简单模型）推广到多催化剂反应，并利用动力学平均场理论对推广后的模型进行分析。在热力学极限和密集网络极限下，我们推导出精确的有效方程，并针对任意度分布分析其不动点。在营养贫乏条件下，无论每个反应涉及的催化剂数量如何，网络异质性都会抑制代谢-饥饿转变。相比之下，在营养丰富条件下，分岔结构随催化剂数量而变化。当每个反应只有一个催化剂时，仅发生连续转变；而当有两个或更多催化剂时，则会出现双稳态相和不连续转变。两个与三个催化剂的分岔结构也有所不同，三个催化剂允许在不同细胞生长速率的代谢状态之间实现双稳态。我们的结果为代谢动力学中的双稳态和突变切换提供了一种可能的机制。
英文摘要
We generalize the Furusawa--Kaneko model, a simple model of intracellular catalytic reaction networks, to multicatalyst reactions and analyze the generalized model using dynamical mean-field theory. In the thermodynamic and dense-network limit, we derive exact effective equations and analyze their fixed points for arbitrary degree distributions. Under nutrient-poor conditions, network heterogeneity suppresses the metabolic--starvation transition irrespective of the number of catalysts per reaction. In contrast, under nutrient-rich conditions, the bifurcation structure changes with the number of catalysts. With one catalyst per reaction, only continuous transitions occur, whereas two or more catalysts give rise to bistable phases and discontinuous transitions. The bifurcation structure also differs between two and three catalysts per reaction, with three catalysts allowing bistability between metabolic states with different cell growth rates. Our results provide a possible mechanism for bistability and abrupt switching in metabolic dynamics.
