This proposal details the development of a high-throughput, growth-based assay for measuring enzyme kinetics of Escherichia coli dihydrofolate reductase (DHFR) in vivo using the GROQ-seq platform. By linking DHFR activity and abundance to growth through engineered gene circuits, the system enables inference of catalytic parameters—kcat, Km, and enzyme abundance—from growth rate data. It includes both abundance and function selection modules, using antibiotic resistance fusions and substrate titration strategies, respectively. This approach allows disambiguation of mutational effects on enzyme kinetics and stability, overcoming limitations of traditional fitness-based assays. The work captures data from single, double, and multimutant DHFR variants and provides a scalable framework for extending in vivo biochemistry to other essential, growth-linked enzymes. This effort is a step toward comprehensive sequence–function mapping for enzymes, supporting applications in evolutionary biology, enzyme engineering, and disease variant interpretation.