Hooshangi Sara, Thiberge Stephan, Weiss Ron
Departments of Electrical Engineering and Molecular Biology, Princeton University, J-319, E-Quad, Princeton, NJ 08544, USA.
Proc Natl Acad Sci U S A. 2005 Mar 8;102(10):3581-6. doi: 10.1073/pnas.0408507102. Epub 2005 Feb 28.
The precise nature of information flow through a biological network, which is governed by factors such as response sensitivities and noise propagation, greatly affects the operation of biological systems. Quantitative analysis of these properties is often difficult in naturally occurring systems but can be greatly facilitated by studying simple synthetic networks. Here, we report the construction of synthetic transcriptional cascades comprising one, two, and three repression stages. These model systems enable us to analyze sensitivity and noise propagation as a function of network complexity. We demonstrate experimentally steady-state switching behavior that becomes sharper with longer cascades. The regulatory mechanisms that confer this ultrasensitive response both attenuate and amplify phenotypical variations depending on the system's input conditions. Although noise attenuation allows the cascade to act as a low-pass filter by rejecting short-lived perturbations in input conditions, noise amplification results in loss of synchrony among a cell population. The experimental results demonstrating the above network properties correlate well with simulations of a simple mathematical model of the system.
信息流通过受响应敏感性和噪声传播等因素支配的生物网络的精确性质,极大地影响着生物系统的运行。在自然发生的系统中,对这些特性进行定量分析往往很困难,但通过研究简单的合成网络可以大大简化分析过程。在这里,我们报告了由一个、两个和三个抑制阶段组成的合成转录级联的构建。这些模型系统使我们能够分析作为网络复杂性函数的敏感性和噪声传播。我们通过实验证明了稳态切换行为,这种行为随着级联长度的增加而变得更加明显。赋予这种超敏感响应的调节机制根据系统的输入条件既会减弱也会放大表型变异。虽然噪声衰减通过拒绝输入条件中的短暂扰动使级联能够充当低通滤波器,但噪声放大导致细胞群体之间失去同步。证明上述网络特性的实验结果与该系统简单数学模型的模拟结果高度相关。