Modeling NFkappaB signaling to capture its dynamical features
Macrophages are immune sentinel cells that are distributed in every organ. Their physiological function is to detect pathogens, tissue damage, and immune cytokines to initiate and coordinate a multi-phased immune response that is appropriate for the immune threat. How macrophages specify the appropriate response remains unknown. However, recent experimental studies indicate that the dynamics of the signal-responsive transcription factor, nuclear factor kappa B (NFkappaB), constitute a temporal code that conveys to the nucleus information about the presence and type of immune threat in the extra-cellular environment. Here, I constructed a pipeline to fit a high resolution mathematical model of the NFkappaB signaling pathway to single cell experimental data. To address model fitting challenges due to high cell-to-cell variability, I developed a novel feature based objective function based on six so-called ‘signaling codons’ (i.e. duration, peak, total activity, oscillation content, etc.) identified as crucial for NFkappaB stimulus specificity using mutual information and classification analysis. In addition, I documented the performance of varying optimization algorithms on our large parameter space of 95 biochemical reactions and identified sensitive parameters that specifically tune informative signaling codons. Applications of this high-resolution model include identifying key circuit design principles that encode the observed stimulus-specific use of signaling codons and pinpointing crucial sources of molecular noise that diminish NFkappaB information encoding.