bioRxivPharmacology & ToxicologyPreprint
A computational workflow for assessing drug effects on temporal signaling dynamics reveals robustness in stimulus-specific NFκB signaling
Emily R. BozichiD, Xiaolu GuoiD, Jennifer L. WilsoniD, Alexander HoffmanniD
Abstract
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 NF{kappa}B 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 NF{kappa}B activation dynamics and its ability to accurately code ligand identity and dose. Specifically, we simulated the dynamic NF{kappa}B 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 NF{kappa}B 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 NF{kappa}B dynamics confusion under pharmacological perturbations. Using these tools we found that temporal coding capacity of the NF{kappa}B signaling network is generally robust to a variety of pharmacological perturbations, thereby enabling the targeting of stimulus-specific dynamics without causing broad side-effects.
- organism: human
- assay: bulk RNA-seq
- research focus: drug response / drug discovery
- approach: deep learning
- approach: statistical model
- Citations
- 0
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