Abstract Quantitative modeling of gene circuits is fundamentally important to synthetic biology, as it offers the potential to transform circuit engineering from trial-and-error construction to rational design and, hence, facilitates the advance of the field. Currently, typical models regard gene circuits as isolated entities and focus only on the biochemical processes within the circuits. Although highly valuable, such a `standard' paradigm has shown to be often incapable of quantitatively, or sometimes even qualitatively, describing circuit behaviors. This limitation arises from multiple factors, among which the overlook of the intimate coupling between circuits and their host is a major cause. My research program aims to discover the fundamental design principles of bacterial gene circuits by harnessing the power of math-based reasoning and tight integration of experiment with theory. In this project, we plan to develop an integrative modeling framework that quantitatively describes gene circuit behaviors in the context of bidirectional circuit-host coupling across multiple scales. To achieve our goal, we will employ a multidisciplinary approach that combines mathematical modeling and experimental molecular biology. We will also build our research on our recent success in the creation of a promising preliminary circuit-host model. For the next few years, our research is organized into three separate but interconnected themes: (1) Develop a generalized framework of circuit-host resource allocation, (2) Build a capacity to account for circuits in varying environments, and (3) Establish a understanding of gene circuit behaviors in ecological contexts. These themes of research will involve the development of generalized theoretical foundations (Theme 1) as well as the investigation of specific key challenges relating to future real-world applications (Theme 2 and 3). The proposed work promises to yield an integrative mathematical framework that quantitatively describes and predicts circuit behaviors with the incorporation of host physiology and circuit-host coupling across multiple scales. Such a framework will help to shift the paradigms of gene circuit engineering from trial-and-error creation to rational design and forward engineering. Additionally, it will advance our understanding of the regulatory dynamics underlying bacterial gene networks and also offer quantitative insights into complex bacterial physiology.