Insulin and other hormones control target cells through a network of signal-mediating molecules. Such networks are extremely complex due to multiple feedback loops in combination with redundancy, shared signal mediators, and cross-talk between signal pathways. We present a novel framework that integrates experimental work and mathematical modeling to quantitatively characterize the role and relation between coexisting submechanisms in complex signaling networks. The approach is independent of knowing or uniquely estimating model parameters because it only relies on (i) rejections and (ii) core predictions (uniquely identified properties in unidentifiable models). The power of our approach is demonstrated through numerous iterations between experiments, modelbased data analyses, and theoretical predictions to characterize the relative role of co-existing feedbacks governing insulin signaling. We examined phosphorylation of the insulin receptor and insulin receptor substrate-1 and endocytosis of the receptor in response to various different experimental perturbations in primary human adipocytes. The analysis revealed that receptor endocytosis is necessary for two identified feedback mechanisms involving mass and information transfer, respectively. Experimental findings indicate that interfering with the feedback may substantially increase overall signaling strength, suggesting novel therapeutic targets for insulin resistance and type 2 diabetes. Because the central observations are present in other signaling networks, our results may indicate a general mechanism in hormonal control.Hormonal control of target cells involves signal transduction from ligand-activated receptors to control of rate-limiting enzymes or proteins that affect key steps in metabolism or other processes within the cell. The signal transduction is carried out by a network of interacting signal mediators. A high degree of complexity is due to the presence of feedback and feed-forward loops, both negative and positive, and the fact that the importance of different interactions changes over time and according to intracellular location. This, in combination with redundancy, shared signal mediators, shared signal paths, and ample cross-talk between signals, leads to a complexity that poses new challenges to progress in dissecting and understanding cellular control. Many diseases, such as cancer and insulin resistance and type 2 diabetes, arise from malfunctioning in signaling networks.Insulin controls target cells through binding to its receptor at the cell surface (1), which activates the intracellular domains of the insulin receptor (IR) 4 to trans-autophosphorylate at specific tyrosine residues. The receptor can then transduce the insulin signal into the cell and to its various effectuating systems, such as glucose uptake and antilipolysis. Foremost of the directly downstream signal-mediating proteins are members of the insulin receptor substrate (IRS) family, in particular IRS1, which is rapidly phosphorylated at specific tyrosine residues by...
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