Information Transmission by Heterogeneous Cell Populations

Reliable signal transduction through biological networks is crucial for accurate interpretation of environmental cues and downstream cellular decision making. Information theory provides a natural framework to quantify how much does the cell know about its extracellular environment; the so-called channel capacity represents the upper limit of the information transmitted through any signaling network channel. Surprisingly, previous work on several mammalian cell signaling networks found very low channel capacities. However, mammalian cells are known to respond precisely to several levels of an environmental signal, which indicates the level of information gained from the environment is higher than previous results would indicate. To address this discrepancy, we develop a new theoretical framework that separately accounts for intrinsic stochastic noise in signaling networks and extrinsic cell-to-cell variability when quantifying channel capacity. We estimate the channel capacity of two important mammalian pathways, the epidermal growth factor pathway, and the insulin-like growth factor pathway. We find that by treating each cell as a separate channel and by explicitly accounting for extrinsic cell-to-cell differences, our method leads to conceptually clearer and significantly higher estimates of channel capacities. We discuss the consequences for downstream cellular decision making.