Abstract: Changes of the nutrient environment have long been used to study regulation and adaptation phenomena in microorganisms and they remain a topic of active investigation in the modern era. While much is known about the molecular interactions governing the regulation of key metabolic processes in response to applied perturbations, they are insufficiently quantified for predictive bottom-up modeling. I will describe a top-down modeling approach, expanding the recently established coarse-grained proteome allocation models from steady-state growth into the kinetic regime. Using only qualitative knowledge of the underlying regulatory processes and imposing the condition of flux balance, we derive a quantitative model of bacterial growth transitions independent of inaccessible kinetic parameters. The resulting flux-controlled regulation model accurately predicts the time course of gene expression and biomass accumulation in response to carbon upshifts and downshifts (e.g., diauxic shifts) without adjustable parameters. As predicted by the model and validated by quantitative proteomics, cells exhibit suboptimal recovery kinetics in response to nutrient shifts due to a rigid strategy of protein synthesis allocation, which is not directed towards alleviating specific metabolic bottlenecks. Our approach is independent of kinetic parameters and thus outlines a theoretical framework for describing a broad range of such kinetic processes without detailed knowledge of the underlying biochemical reactions.