Macrophages function as immune sentinel cells, initiating appropriate and specialized immune responses to a great variety of pathogens. The transcription factor NFκB controls macrophage gene expression responses, and its temporal dynamic enables stimulus-specificity of these responses. Using a fluorescent reporter mouse our laboratory recently generated large amounts of single-cell NFκB dynamic data and identified dynamic features, termed ‘signaling codons’, that convey information to the nucleus about stimulus ligand and dose. Here, we aimed to recapitulate the stimulus-specific but highly cell-to-cell heterogeneous NFκB dynamics with a mathematical model of the signaling network. The parameters that are subject to biological variation provide the potential to account for heterogeneity. We estimated parameter distributions using the Stochastic Approximation Expectation Maximization (SAEM) approach and then fit the individual cell data using Bayesian maximum a posteriori (MAP) estimation. Visual inspection revealed an excellent fit with the data. To quantitatively evaluate the fitting performance, we compared the experimental and predicted distributions of NFκB signaling codons. Further, we identified biochemical reactions that may account for the cellular heterogeneity in NFκB dynamics. Our results establish a mathematical modeling tool that may be used to study the molecular determinants of response specificity and dynamical coding in immune sentinel cells at the single cell level.
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