PDF(Pubmed)
Abstract：
Channel capacity of signaling networks quantifies their fidelity in sensing extracellular inputs. Low estimates of channel capacities for several mammalian signaling networks suggest that cells can barely detect the presence/absence of environmental signals. However, given the extensive heterogeneity and temporal stability of cell state variables, we hypothesize that the sensing ability itself may depend on the state of the cells. In this work, we present an information-theoretic framework to quantify the distribution of sensing abilities from single-cell data. Using data on two mammalian pathways, we show that sensing abilities are widely distributed in the population and most cells achieve better resolution of inputs compared to an \'average cell\'. We verify these predictions using live-cell imaging data on the IGFR/FoxO pathway. Importantly, we identify cell state variables that correlate with cells\' sensing abilities. This information-theoretic framework will significantly improve our understanding of how cells sense in their environment.
摘要：
信号网络的信道容量量化了它们在感测细胞外输入时的保真度。对几种哺乳动物信号网络的信道容量的低估计表明，细胞几乎无法检测到环境信号的存在/不存在。然而,考虑到细胞状态变量的广泛异质性和时间稳定性，我们假设感知能力本身可能取决于细胞的状态。在这项工作中,我们提出了一个信息理论框架来量化单细胞数据中感知能力的分布。利用两种哺乳动物途径的数据，我们表明，感知能力在群体中广泛分布，与“平均细胞”相比，大多数细胞获得了更好的输入分辨率。我们使用IGFR/FoxO途径的活细胞成像数据验证了这些预测。重要的是,我们确定与细胞感知能力相关的细胞状态变量。这种信息理论框架将极大地改善我们对细胞在其环境中如何感知的理解。
