A Mathematical and Engineering Framework to Predict the Effect of Resource Sharing on Genetic Networks

Abstract

In this thesis, a framework is developed to investigate the effect of resource sharing on the performance of genetic networks. A model of a genetic system with shared resources for protein degradation is developed that captures resource sharing effects and is subsequently analyzed to discover ways in which this form of resource sharing effects genetic networks. It is shown that sharing of degradation resources may cancel undesirable effects due to resource sharing of protein production resources. Next, a theoretical framework is developed to find conditions in which a genetic network may exhibit a change in its number of equilibria due to resource sharing effects. Finally, metrics and an experimental method are proposed to estimate the quantity of resources a genetic network uses and the sensitivity of the network to disturbances in resource availability. These measures may be utilized to inform design choices in genetic networks in which resource sharing plays a significant role. These effects become increasingly important in more complex genetic networks. Quantification of such resource sharing effects are an important step in increasing the predictability of genetic networks.