Improving Metabolic Pathway Efficiency by Statistical Model-Based Multivariate Regulatory Metabolic Engineering.

Metabolic engineering entails target modification of cell metabolism to maximize the production of a specific compound. For empowering combinatorial optimization in strain engineering, tools and algorithms are needed to efficiently sample the multidimensional gene expression space and locate the desirable overproduction phenotype. We addressed this challenge by employing design of experiment (DoE) models to quantitatively correlate gene expression with strain performance.