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 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 that optogenetic Wnt signaling allows for regulatory control beyond a simple binary switch and provide a framework to apply ideas from information processing to single-cell in vitro experiments. ... Read more

Cells process dynamic signaling inputs to regulate fate decisions during development. While oscillations or waves in key developmental pathways, such as Wnt, have been widely observed, the principles governing how cells decode these signals remain unclear. By leveraging optogenetic control of the Wnt signaling pathway in both HEK293T cells and H9 human embryonic stem cells, we systematically map the relationship between signal frequency and downstream pathway activation. We find that cells exhibit a minimal response to Wnt at certain frequencies, a behavior we term anti-resonance. We developed both detailed biochemical and simplified hidden variable models that explain how anti-resonance emerges from the interplay between fast and slow pathway dynamics. Remarkably, we find that frequency directly influences cell fate decisions involved in human gastrulation; signals delivered at anti-resonant frequencies result in dramatically reduced mesoderm differentiation. Our work reveals a previously unknown mechanism of how cells decode dynamic signals and how anti-resonance may filter against spurious activation. These findings establish new insights into how cells decode dynamic signals with implications for tissue engineering, regenerative medicine, and cancer biology. ... Read more

The genetic information stored in mRNAs is decoded by ribosomes during mRNA translation. mRNAs are typically translated by multiple ribosomes simultaneously, but it is unclear whether and how the activity of different ribosomes on an mRNA is coordinated. Here, we develop an imaging approach based on stopless-ORF circular RNAs (socRNAs) to monitor translation of individual ribosomes in either monosomes or polysomes with very high resolution. Using experiments and simulations, we find that translating ribosomes frequently undergo transient collisions. However, unlike persistent collisions, such transient collisions escape detection by cellular quality control pathways. Rather, transient ribosome collisions promote productive translation by reducing ribosome pausing on problematic sequences, a process we term ribosome cooperativity. Ribosome cooperativity also reduces recycling of ribosomes by quality control pathways, thus enhancing processive translation. Together, our single-ribosome imaging approach reveals that ribosomes cooperate during translation to ensure fast and efficient translation. ... Read more