A computational workflow for assessing drug effects on temporal signaling dynamics reveals robustness in stimulus-specific NFκB signaling

Single-cell studies of signal transduction have revealed complex temporal dynamics that determine downstream biological function. For example, the stimulus-specific dynamics of the transcription factor NFκB specify stimulus-specific gene expression programs, and loss of specificity leads to disease. Thus, it is intriguing to consider drugs that may restore signaling specificity in disease contexts, or reduce activity but maintain signaling specificity to avoid unwanted side effects. However, while steady-state dose-response relationships have been the focus of pharmacological studies, there are no established methods for quantifying drug impact on stimulus-response signaling dynamics. Here we evaluated how drug treatments affect the stimulus-specificity of NFκB activation dynamics and its ability to accurately code ligand identity and dose. Specifically, we simulated the dynamic NFκB trajectories in response to 15 stimuli representing various immune threats under treatment of 10 representative drugs across 20 dosage levels. To quantify the effects on coding capacity, we introduced a Stimulus Response Specificity (SRS) score and a stimulus confusion score. We constructed stimulus confusion maps by employing epsilon network clustering in the trajectory space and in various dimensionally reduced spaces: canonical polyadic decomposition (CPD), functional principal component analysis (fPCA), and NFκB signaling codons (i.e., established, informative dynamic features). Our results indicated that the SRS score and the stimulus confusion map based on signaling codons are best-suited to quantify stimulus-specific NFκB dynamics confusion under pharmacological perturbations. Using these tools we found that temporal coding capacity of the NFκB signaling network is generally robust to a variety of pharmacological perturbations, thereby enabling the targeting of stimulus-specific dynamics without causing broad side-effects.Author summary: Immune- and stress-response signaling pathways are functionally pleiotropic: they respond to multiple stimuli and mediate distinct biological responses. For innate immune cells distinguishing different immune threats is important, and loss of stimulus-response specificity is linked to autoimmune or inflammatory diseases. This pleiotropy has posed a challenge for the development of safe pharmacologic interventions, and many promising drug compounds have turned out to result in debilitating side effects. Stimulus-response specificity is mediated by the dynamics of cellular signaling, constituting a “temporal code.” This raises the question of whether stimulus responses may be pharmacologically targeted without disrupting stimulus-response specificity, or to restore stimulus-response specificity. However, how to effectively measure and quantify the stimulus-response specificity of signaling dynamics remains unclear. Here, we developed and tested computational metrics on high-throughput simulation data to assess drug effects on the stimulus-response specificity of the NFκB pathway. The results advance both the study of temporal signaling codes and strategies for precision drug targeting.