Department of Biomedical Engineering, Johns Hopkins University, 3400 North Charles Street, Baltimore, MD 21218, USA.
Science. 2011 Oct 21;334(6054):354-8. doi: 10.1126/science.1204553. Epub 2011 Sep 15.
Molecular noise restricts the ability of an individual cell to resolve input signals of different strengths and gather information about the external environment. Transmitting information through complex signaling networks with redundancies can overcome this limitation. We developed an integrative theoretical and experimental framework, based on the formalism of information theory, to quantitatively predict and measure the amount of information transduced by molecular and cellular networks. Analyzing tumor necrosis factor (TNF) signaling revealed that individual TNF signaling pathways transduce information sufficient for accurate binary decisions, and an upstream bottleneck limits the information gained via multiple integrated pathways. Negative feedback to this bottleneck could both alleviate and enhance its limiting effect, despite decreasing noise. Bottlenecks likewise constrain information attained by networks signaling through multiple genes or cells.
分子噪声限制了单个细胞分辨不同强度输入信号的能力，使其难以获取外部环境信息。通过具有冗余的复杂信号网络传递信息，可以克服这一限制。我们基于信息论的形式主义，开发了一个综合的理论和实验框架，用于定量预测和测量分子和细胞网络传递的信息量。通过分析肿瘤坏死因子（TNF）信号，我们发现单个 TNF 信号通路传递的信息量足以做出准确的二元决策，而上游瓶颈限制了通过多个整合通路获得的信息量。尽管噪声降低了，但对该瓶颈的负反馈可以减轻并增强其限制作用。瓶颈同样限制了通过多个基因或细胞进行信号传递的网络所获得的信息量。
