title: High-throughput evaluation of synthetic metabolic pathways.
abstract: A central challenge in the field of metabolic engineering is the efficient identification of a metabolic pathway genotype that maximizes specific productivity over a robust range of process conditions. Here we review current methods for optimizing specific productivity of metabolic pathways in living cells. New tools for library generation, computational analysis of pathway sequence-flux space, and high-throughput screening and selection techniques are discussed.
authors.affiliation: Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Justin R
authors.initials: JR
authors.lastname: Klesmith
authors.affiliation: Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI 48824, USA; Department of Biosystems and Agricultural Engineering, Michigan State University, East Lansing, MI 48824, USA.
authors.forename: Timothy A
authors.initials: TA
authors.lastname: Whitehead
keywords: Computational Optimization; Deep Mutational Scanning; Metabolic Engineering; Protein Engineering; Synthetic Biology