Modeling Multiple Interconnected TLR Signaling Cascades Is Needed to Recapitulate the Effector Function of Bone Marrow-Derived Macrophages

(1) Background: Modeling signaling cascades is helpful in deciphering the structure and interactions within and between cascades, and testing our understanding of the cascades by using the models to make predictions and suggesting experiments to evaluate the efficacy of the models. Here, several interconnected toll-like receptor (TLR) signaling cascades were studied in combination to determine if there was any significant difference from studying them individually. (2) Methods: Our approach was to enhance a tool previously used to construct agent-based models of single-TLR signaling cascades with the ability to combine multiple individual models into a single, more complex model. The tool was used to combine three TLR signaling models, and predictions from the model were then compared against experimental results from all three cascades. The lab experiments focused on one of two different readouts: examining RNA expression or effector function. (3) Results: The results showed that if we used RNA as the readout, the model and experimental data were closely aligned. However, to fit the effector function data, we had to assign more importance to the role of the TLR7 cascade. (4) Conclusions: These results show that modeling can be used to decipher the structure and interactions within and between cascades, but the pattern of response is specific to the experimental readout. The data also show that modeling and experimenting with a combination of cascades is critical to (1) determining the relative importance of each cascade with respect to response to particular agonists and (2) understanding the interactions (both synergistic and antagonistic) between the cascades.