The rapid development of technology and techniques in synthetic biology and metabolic engineering has enabled the bio-based economy to develop microbial cell factories for the biological production of chemicals from renewable sources. As biological techniques and tools have developed and become cheaper, the ability to create strains and mutants has become essentially limitless. Traditional methods for screening and selecting viable mutants are low-throughput compared to the ability to build mutants, causing a bottleneck within the design-build-test-learn engineering cycle. To address the testing bottleneck, biosensors such as transcription factor-based biosensors have emerged as powerful biological tools that can be applied for the screening and control of microbial cell factories. Such biosensors can also be used in other applications for point-of-care diagnostics and environmental pollutant monitoring. While this technology has demonstrated its potential in the literature, the widespread development and deployment of biosensors is still limited by the availability of transcription factors for detecting target chemicals and the inconsistent design methods of biosensors. This project seeks to overcome current bottlenecks using multiple strategies to elucidate fundamental principles of transcription factor biosensor specificity and circuit engineering that can be harnessed to develop future biosensors. This was accomplished by establishing strategies for the design and construction of biosensors to guide biosensor development, developing structure-guided computational approaches for transcription factor specificity engineering to expand the breadth of potential biosensor applications, and creating chimeric transcription factors to expedite biosensor discovery and overcome the currently high levels of characterization typically required to develop biosensors. The accomplishment of these tasks improves the ability to design, engineer, and discover biosensors for molecules of interest, accelerating biosensor development and the implementation of biosensors towards harnessing biology for various applications.