Systems Characterization of Cell Surface Receptors

In a paper publishing today (June 1) in the Open Access journal PLoS Computational Biology, Drs. Shankaran, Resat and Wiley from the Pacific Northwest National Laboratory employ a generalized mathematical model to comparatively explore the design principles of signal transduction and transport receptors.

The authors use a new module-based systems theory approach along with quantitative metrics for network function and robustness to show that endocytosis and other receptor/ligand properties can be described by just a few control parameters. Using mathematical analysis, the authors show that the efficiency and robustness of receptor systems are encoded by two fundamental parameters: the avidity which quantifies the ability of a receptor system to capture ligand, and the consumption which quantifies the ability to internalize bound ligand.

By examining a number of receptor systems, the authors demonstrate that the response of receptor systems can be characterized as being: i) avidity-controlled, which depends primarily on ligand capture efficiency, ii) consumption-controlled where the ability to internalize surface-bound ligand is the primary control parameter, and iii) dual-sensitive, in which both the avidity and consumption parameters are important. The location of various receptor systems in control parameter space dictates their specific function and regulation.

Most significantly, the authors argue that the evolution of a given receptor system can be understood in terms of its optimal location in avidity-consumption parameter space. For example, induced endocytosis can be shown to be an optimal solution for achieving high fidelity information transmission for signaling receptors. Overall, this study develops and applies a new strategy for quantifying the phenotype of complex systems that should be generally applicable to a wide range of problems in systems biology research.

The research was funded by the National Institutes of Health and the Biomolecular Systems Initiative at PNNL.