Nacher J C, Ochiai T, Yamada T, Kanehisa M, Akutsu T
Bioinformatics Center, Institute for Chemical Research, Kyoto University, Gokasho, Uji, Kyoto 611-0011, Japan.
Biosystems. 2006 Jan;83(1):26-37. doi: 10.1016/j.biosystems.2005.09.003. Epub 2005 Oct 19.
The study of the scale-free topology in non-biological and biological networks and the dynamics that can explain this fascinating property of complex systems have captured the attention of the scientific community in the last years. Here, we analyze the biochemical pathways of three organisms (Methanococcus jannaschii, Escherichia coli, Saccharomyces cerevisiae) which are representatives of the main kingdoms Archaea, Bacteria and Eukaryotes during the course of the biological evolution. We can consider two complementary representations of the biochemical pathways: the enzymes network and the chemical compounds network. In this article, we propose a stochastic model that explains that the scale-free topology with exponent in the vicinity of gamma approximately 3/2 found across these three organisms is governed by the log-normal dynamics in the evolution of the enzymes network. Precisely, the fluctuations of the connectivity degree of enzymes in the biochemical pathways between evolutionary distant organisms follow the same conserved dynamical principle, which in the end is the origin of the stationary scale-free distribution observed among species, from Archaea to Eukaryotes. In particular, the log-normal dynamics guarantees the conservation of the scale-free distribution in evolving networks. Furthermore, the log-normal dynamics also gives a possible explanation for the restricted range of observed exponents gamma in the scale-free networks (i.e., gamma > or = 3/2). Finally, our model is also applied to the chemical compounds network of biochemical pathways and the Internet network.
近年来,对非生物和生物网络中无标度拓扑结构以及能够解释复杂系统这一迷人特性的动力学的研究,引起了科学界的关注。在这里,我们分析了三种生物(詹氏甲烷球菌、大肠杆菌、酿酒酵母)的生化途径,它们分别是生物进化过程中古菌、细菌和真核生物这三个主要生物界的代表。我们可以考虑生化途径的两种互补表示:酶网络和化合物网络。在本文中,我们提出了一个随机模型,该模型解释了在这三种生物中发现的指数在γ约为3/2附近的无标度拓扑结构是由酶网络进化中的对数正态动力学所支配的。确切地说,进化距离较远的生物之间生化途径中酶连接度的波动遵循相同的守恒动力学原理,最终这也是从古菌到真核生物物种间观察到的稳定无标度分布的起源。特别地,对数正态动力学保证了进化网络中无标度分布的守恒。此外,对数正态动力学也为无标度网络中观察到的指数γ的受限范围(即γ≥3/2)提供了一种可能的解释。最后,我们的模型还应用于生化途径的化合物网络和互联网网络。