Building kinetic models for metabolic engineering

Kinetic formalisms of metabolism link metabolic fluxes to enzyme levels, metabolite concentrations and their allosteric regulatory interactions. Though they require the identification of physiologically relevant values for numerous parameters, kinetic formalisms uniquely establish a mechanistic link across heterogeneous omics datasets and provide an overarching vantage point to effectively inform metabolic engineering strategies. Advances in computational power, gene annotation coverage, and formalism standardization have led to significant progress over the past few years. However, careful interpretation of model predictions, limited metabolic flux datasets, and assessment of parameter sensitivity remain as challenges. In this review we highlight fundamental considerations which influence model quality and prediction, advances in methodologies, and success stories of deploying kinetic models to guide metabolic engineering.

Automated summary

Kinetic formalisms of metabolism provide a mechanistic link across heterogeneous omics datasets to inform metabolic engineering strategies. Despite challenges in identifying physiologically relevant values for parameters, recent progress in computational power, gene annotation coverage, and formalism standardization have enabled significant advancements. Careful interpretation of model predictions, limited metabolic flux datasets, and assessment of parameter sensitivity remain as challenges that need to be addressed.