Projects per year
Information theoretic approaches can be used to quantify information transfer via cell signaling networks. Here we do so for gonadotropin-releasing hormone (GnRH) activation of ERK (extracellular signal-regulated kinase) and NFAT (nuclear factor of activated T-cells) in large numbers of individual fixed LβT2 and HeLa cells. Information transfer, measured by mutual information between GnRH and ERK or NFAT, was <1Bit (in spite of 3 Bit system inputs). It was increased by sensing both ERK and NFAT but the increase was <50%. In live cells information transfer via GnRH receptors to NFAT was also <1Bit and was increased by consideration of response trajectory, but the increase was <10%. GnRH secretion is pulsatile so we explored information gained by sensing a second pulse, developing a model of GnRH signaling to NFAT with variability introduced by allowing effectors to fluctuate. Simulations revealed that when cell-cell variability reflects rapidly fluctuating effector levels, additional information is gained by sensing two GnRH pulses but where it is due to slowly fluctuating effectors, responses in one pulse are predictive of those in another, so little information is gained from sensing both. Wet-lab experiments revealed that the latter scenario holds true for GnRH signaling; within the timescale of our experiments (1-2hr) cell-cell variability in the NFAT pathway remains relatively constant so trajectories are reproducible from pulse to pulse. Accordingly, joint sensing, sensing of response trajectories and sensing of repeated pulses can all increase information transfer via GnRHR but in each case the increase is small.
- extracellular signal‐regulated kinase (ERK)
- nuclear factor of activated T-cells (NFAT)
- G protein-coupled receptor (GPCR)
- gonadotropin-releasing hormone (GnRH)
- mitogen-activated protein kinase (MAPK)
- mathematical modeling