Institute of Theoretical Physics, Lanzhou University, Lanzhou, China.
PLoS One. 2012;7(12):e51840. doi: 10.1371/journal.pone.0051840. Epub 2012 Dec 20.
It is well known that noise is inevitable in gene regulatory networks due to the low-copy numbers of molecules and local environmental fluctuations. The prediction of noise effects is a key issue in ensuring reliable transmission of information. Interlinked positive and negative feedback loops are essential signal transduction motifs in biological networks. Positive feedback loops are generally believed to induce a switch-like behavior, whereas negative feedback loops are thought to suppress noise effects. Here, by using the signal sensitivity (susceptibility) and noise amplification to quantify noise propagation, we analyze an abstract model of the Myc/E2F/MiR-17-92 network that is composed of a coupling between the E2F/Myc positive feedback loop and the E2F/Myc/miR-17-92 negative feedback loop. The role of the feedback loop on noise effects is found to depend on the dynamic properties of the system. When the system is in monostability or bistability with high protein concentrations, noise is consistently suppressed. However, the negative feedback loop reduces this suppression ability (or improves the noise propagation) and enhances signal sensitivity. In the case of excitability, bistability, or monostability, noise is enhanced at low protein concentrations. The negative feedback loop reduces this noise enhancement as well as the signal sensitivity. In all cases, the positive feedback loop acts contrary to the negative feedback loop. We also found that increasing the time scale of the protein module or decreasing the noise autocorrelation time can enhance noise suppression; however, the systems sensitivity remains unchanged. Taken together, our results suggest that the negative/positive feedback mechanisms in coupled feedback loop dynamically buffer noise effects rather than only suppressing or amplifying the noise.
众所周知，由于分子的低拷贝数和局部环境波动，噪声在基因调控网络中是不可避免的。噪声效应的预测是确保信息可靠传输的关键问题。相互关联的正反馈回路和负反馈回路是生物网络中重要的信号转导基元。正反馈回路通常被认为会诱导开关样行为，而负反馈回路则被认为会抑制噪声效应。在这里，我们通过使用信号灵敏度（susceptibility）和噪声放大来量化噪声传播，分析了由 E2F/Myc 正反馈回路和 E2F/Myc/miR-17-92 负反馈回路之间的耦合组成的 Myc/E2F/MiR-17-92 网络的抽象模型。反馈回路对噪声效应的作用取决于系统的动态特性。当系统处于高蛋白浓度的单稳或双稳状态时，噪声始终受到抑制。然而，负反馈回路降低了这种抑制能力（或提高了噪声传播）并增强了信号灵敏度。在兴奋性、双稳或单稳的情况下，低蛋白浓度会增强噪声。负反馈回路降低了这种噪声增强以及信号灵敏度。在所有情况下，正反馈回路的作用都与负反馈回路相反。我们还发现，增加蛋白质模块的时间尺度或降低噪声自相关时间可以增强噪声抑制；然而，系统的灵敏度保持不变。总之，我们的结果表明，耦合反馈回路中的负/正反馈机制动态缓冲噪声效应，而不仅仅是抑制或放大噪声。
