Quantifying temporal information accumulation for biochemical signaling dynamics

The temporal patterns of intracellular signaling contains information for cell decision making. When signaling is initiated by a stimulus, circuits that decode the temporal patterns to control biological effectors must make decisions based on available information within the timecourse. Quantifying information flow through signaling networks thus requires a dynamical framework to estimate information transmission in a time-dependent manner. We find that a type of stochastic process can be used to represent the signaling activities that show a high degree of cell-to-cell variability. Based on the model, we extract the time-dependent channel capacity of signaling pathways. When the transcription factor NFκB is activated by diverse immune threats in macrophages (e.g. virus, gram negative or positive bacteria, or cytokine), the channel capacity reaches 1 bit of information around 1 hour and 2 bits of information within 10 hours. By knocking down the feedback regulation in the signaling pathway, the information accumulation was reduced, which uncovers that information transmission is enhanced by feedback control. The result demonstrates that the method allows quantification on the learning rate of decoding circuits for rapid cellular decision making.