Synthetic biology of metabolism: using natural variation to reverse engineer systems.
A goal of metabolic engineering is to take a plant and introduce new or modify existing pathways in a directed and predictable fashion. However, existing data does not provide the necessary level of information to allow for predictive models to be generated. One avenue to reverse engineer the necessary information is to study the genetic control of natural variation in plant primary and secondary metabolism. These studies are showing that any engineering model will have to incorporate information about 1000s of genes in both the nuclear and organellar genome to optimize the function of the introduced pathway. Further, these genes may interact in an unpredictable fashion complicating any engineering approach as it moves from the one or two gene manipulation to higher order stacking efforts. Finally, metabolic engineering may be influenced by a previously unrecognized potential for a plant to measure the metabolites within it. In combination, these observations from natural variation provide a beginning to help improve current efforts at metabolic engineering.
Department of Plant Sciences, University of California at Davis, Davis, CA 95616, USA; DynaMo Center of Excellence, University of Copenhagen, Thorvaldsensvej 40, DK-1871 Frederiksberg C, Denmark. Electronic address: kliebenstein@ucdavis.edu.
Daniel J
DJ
Kliebenstein
D014644:Genetic Variation; D055106:Genome-Wide Association Study; D060847:Metabolic Engineering; D040641:Quantitative Trait Loci; D058615:Synthetic Biology