These differences are due, in part, to the result of cell-type dependent expression and localization of key regulatory molecules. For example, in contrast to the cell-surface localization of TLR3 on monocyte/macrophages, TLR3 expression is endosomal in epithelial cells. Procyanidin-B1 Moreover, cell-type differences have been observed in the IRF3 pathway modulating IKKc/ NEMO alternative splice product. For these reasons, we will focus on the epithelium, the primary sentinel cell of respiratory RNA virus interactions. Cross-talk between the NF-kB and IRF3 signaling arms is critical for determining the cellular outcome of viral infection. Studies in NF-kB – deficient cells have shown that the initial kinetics of the type I interferon response depends on concurrent NF-kB activation. In the absence of NF-kB, the rapid response of IFNb expression is blunted, reducing the propagation of anti-viral signals in the mucosal surface. Moreover, NF-kB controls expression of the downstream IFN auto-amplification loop through STAT1, IRF-1, 5, and -7 transcription factors. These findings indicate that the two NF-kB and IRF3 signaling arms are highly interconnected and that these interconnections influence the kinetics of the IIR. The specific purpose of this study is to apply an estimationvalidation modeling approach to investigate IIR Glycitin network topology and interaction rates are consistent with the observed responses of both pathways of human A549 airway epithelial cells in response to dsRNA stimulation, which is a synchronized model of viral infection. dsRNA is a molecular pa ern that activates both TLR3 and RIG-I-MAVS signaling in airway epithelial cells and is chosen as a model for viral infection for two reasons. First, it mimics the viral intermediate-products sensed by the innate immune-response mechanism without confounding effects of IIR antagonism produced by the viral proteins, and second, the dsRNA stimulation is synchronous for all cells in the population. Our strategy for determining this topology is composed of two elements: measurements of the time series of major mRNA and protein species in responses to various doses of dsRNA, and knocking down expression of selected nodes of the pathway, followed by analysis of the responses of the perturbed system. The time courses of mRNA and protein expression of unperturbed and perturbed systems are measured by quantitative real time PCR and stable isotope dilution-selective reaction monitoring for fi ing the model parameters. Quantitative SID-SRM measurements are much more accurate than other conventional blo ing methods; this represents the first example to our knowledge of using SRMs for modeling signaling systems. For the siRNA silencing experiments, essential for validation of the model, hAECs were transfected with siRNAs specifically targeting the Pa ern Recognition Receptors, the regulatory subunit of IkB kinase complex, and components of the NF-kB pathway and IRF3 pathway. Our model represents the observed phenomena of dsRNA-inducible RelA and IRF3 activation, negative NF-kB -IRF3 cross-talk, distinct phases of inducible RIG-I degradation and resynthesis. The presence of negative cross-talk is independently confirmed by evolutionary footprint analysis, where we can identify candidate binding sites for NF-kB on IRF genes and vice-versa.