Integrative Approach to Extract the Single-cell Dynamics of LPS-induced NF kappa B Signal Pathway through Flow Cytometry Measurements and Parameter Estimation
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2018 AACC. It is well established that the dynamics of signaling and gene expression in a clonal population of cells vary both in the absence and presence of stimuli. In order to elucidate the stochasticity in signaling and downstream cellular responses, we have formulated a mathematical model and utilized it along with single-cell experimental measurements to investigate the cell-to-cell variability in the response of mouse macrophages to lipopolysaccharide (LPS). Since the single-cell mathematical model is computationally expensive to simulate, a semi-stochastic model that combines a deterministic model with parameters that have distributions at the single-cell level is more viable than a stochastic model. This modeling approach requires an accurate deterministic model a priori. Motivated by above considerations, this work aimed to quantitatively calibrate the deterministic model that can simulate the average single-cell dynamics via a systematic approach, which combines single-cell experimental measurements and a parameter selection method, with the LPS-induced NF B signal pathway as an example case.
