Benchmarking the communication fidelity of biomolecular signaling cascades featuring pseudo-one-dimensional transport

Synthetic biologists endeavor to predict how the increasing complexity of multi-step signaling cascades impacts the fidelity of molecular signaling, whereby information about the cellular state is often transmitted with proteins that diffuse by a pseudo-one-dimensional stochastic process. This begs the question of how the cell leverages passive transport mechanisms to distinguish informative signals from the intrinsic noise of diffusion. We address this problem by using a one-dimensional drift-diffusion model to derive an approximate lower bound on the degree of facilitation needed to achieve single-bit informational efficiency in signaling cascades as a function of their length. Within the assumptions of our model, we find that a universal curve of the Shannon-Hartley form describes the information transmitted by a signaling chain of arbitrary length and depends upon only a small number of physically measurable parameters. This enables our model to be used in conjunction with experimental measurements to aid in the selective design of biomolecular systems that can overcome noise to function reliably, even at the single-cell level.