Program in Computational Biology and Bioinformatics, Department of Molecular Biophysics and Biochemistry, Yale University, Bass 432, 266 Whitney Avenue, New Haven, CT 06520, USA.
Proc Natl Acad Sci U S A. 2010 May 18;107(20):9186-91. doi: 10.1073/pnas.0914771107. Epub 2010 May 3.
The genome has often been called the operating system (OS) for a living organism. A computer OS is described by a regulatory control network termed the call graph, which is analogous to the transcriptional regulatory network in a cell. To apply our firsthand knowledge of the architecture of software systems to understand cellular design principles, we present a comparison between the transcriptional regulatory network of a well-studied bacterium (Escherichia coli) and the call graph of a canonical OS (Linux) in terms of topology and evolution. We show that both networks have a fundamentally hierarchical layout, but there is a key difference: The transcriptional regulatory network possesses a few global regulators at the top and many targets at the bottom; conversely, the call graph has many regulators controlling a small set of generic functions. This top-heavy organization leads to highly overlapping functional modules in the call graph, in contrast to the relatively independent modules in the regulatory network. We further develop a way to measure evolutionary rates comparably between the two networks and explain this difference in terms of network evolution. The process of biological evolution via random mutation and subsequent selection tightly constrains the evolution of regulatory network hubs. The call graph, however, exhibits rapid evolution of its highly connected generic components, made possible by designers' continual fine-tuning. These findings stem from the design principles of the two systems: robustness for biological systems and cost effectiveness (reuse) for software systems.
基因组通常被称为生物体的操作系统 (OS)。计算机 OS 由称为调用图的监管控制网络来描述，它类似于细胞中的转录调控网络。为了将我们对软件系统架构的第一手知识应用于理解细胞设计原则，我们根据拓扑结构和进化，将一个研究充分的细菌（大肠杆菌）的转录调控网络与一个规范的 OS（Linux）的调用图进行了比较。我们表明，这两个网络都具有基本的分层布局，但存在一个关键区别：转录调控网络在顶部有几个全局调控器，在底部有许多目标；相反，调用图有许多调控器控制一小部分通用功能。这种头重脚轻的组织导致调用图中的功能模块高度重叠，而在调控网络中则相对独立。我们进一步开发了一种在两个网络之间进行可比进化率测量的方法，并根据网络进化来解释这种差异。通过随机突变和随后的选择进行的生物进化过程严格限制了调控网络枢纽的进化。然而，调用图表现出其高度连接的通用组件的快速进化，这是由于设计者的不断微调成为可能。这些发现源于这两个系统的设计原则：生物系统的稳健性和软件系统的成本效益（重用）。
