Optimizing information transmission in optogenetic Wnt signaling

Abstract

Populations of cells regulate gene expression in response to external signals, but their ability to make reliable collective decisions is limited by both intrinsic noise in molecular signaling and variability between individual cells. In this work, we use optogenetic control of the canonical Wnt pathway as an example to study how reliably information about an external signal is transmitted to a population of cells, and determine an optimal encoding strategy to maximize information transmission from Wnt signals to gene expression. We find that it is possible to reach an information capacity beyond 1 bit only through an appropriate, discrete encoding of signals: using either no Wnt, a short Wnt pulse, or a sustained Wnt signal. By averaging over an increasing number of outputs, we systematically vary the effective noise in the pathway. As the effective noise decreases, the optimal encoding comprises more discrete input signals. These signals do not need to be fine-tuned to achieve near-optimal information transmission. The optimal code transitions into a continuous code in the small-noise limit, which can be shown to be consistent with the Jeffreys prior. We visualize the performance of different signal encodings using decoding maps. Our results suggest optogenetic Wnt signaling allows for regulatory control beyond a simple binary switch, and provides a framework to apply ideas from information processing to single-cell in vitro experiments.

References in corpus (15)

• Recurrence Plots for the Analysis of Complex Systems
• Universally Sloppy Parameter Sensitivities in Systems Biology
• Statistical physics of inference: Thresholds and algorithms
• Information flow and optimization in transcriptional control
• Optimal decoding of information from a genetic network
• Mutual information between in- and output trajectories of biochemical networks
• Information transmission in genetic regulatory networks: a review
• Information capacity of genetic regulatory elements
• Optimizing information flow in small genetic networks. II: Feed forward interactions
• The role of spatial averaging in the precision of gene expression patterns
• Maximizing the information learned from finite data selects a simple model
• Precise and scalable self-organization in mammalian pseudo-embryos
• Path Weight Sampling: Exact Monte Carlo Computation of the Mutual Information between Stochastic Trajectories
• A scaling law from discrete to continuous solutions of channel capacity problems in the low-noise limit
• Weak transcription factor clustering at binding sites can facilitate information transfer from molecular signals