Optimizing Biosensor Measurements for Multicomponent Reactions

University Of Delaware, Newark DE

Investigators

Abstract

Since surface plasmon resonance (SPR) and similar biosensors typically measure only mass changes, it can be difficult to analyze data from multiple simultaneous reactions. This project considers the example of polymerase switching in translesion DNA synthesis, which is essential for cells to cope with DNA damage. The polymerase switch process involves multiple components. A "tool-belt" model has been proposed for the switch, but attempting to verify the model with conventional fluoroscopy modifies the normal activity of the proteins. Thus, a label-free technique such as SPR is desirable, but requires more sophisticated mathematical modeling. A mathematical model will be produced that relates the sensogram signal to the underlying kinetics. Asymptotic analysis and numerical simulations of this model will be used to design a set of experiments that can determine the kinetic pathway for a general system. These results will be used to test the "tool-belt" model. In particular, by adjusting the relative concentrations of the various species, one can move into regimes where a few reactions dominate. Then the rate constants can be easily ascertained, since the nonlinear governing equations will be simplified. When studying the processes underpinning disease and other biological systems, biochemists often need accurate estimates of reaction rates. Optical biosensors are a popular way to measure such reactions, as they do not disturb the underlying system. Correctly interpreting biosensor data requires having an accurate mathematical model for the system. Current models do not work well when multiple reactions are occurring simultaneously. A new model will be developed that will provide scientists a general roadmap on how to design experiments to analyze multiple reactions that occur at the same time. In particular, the mathematics will be used to validate a model to explain translesion DNA synthesis, which is essential for cells to cope with DNA damage.