One of the key features of metabolic engineering is the modication of metabolic networks through addition, deletion, and/or alteration of metabolic pathways with the purpose of improving production of specic metabolites. ese manipulations are oen archived by using recombinant DNA technologies and chemical engineering methods [1,2]. However, due to the complexity metabolic networks and their regulation, modications of metabolic pathways can have unpredictable consequences that may hamper achieving the original engineering goals. Prior to the advent of systemic approaches, metabolic engineering relied on intuition and biochemical knowledge for the selection of metabolic pathways for manipulation. Results of this approach were oen unexpected and the resulting strains required extensive ne tuning to yield viable production strains. Implementation of complicated metabolic engineering designs involves genetic modications that are associated with signicant phenotypic changes of the organism. Such changes can result in slower growth rates and production of unnecessary and potentially toxic by-products among other complications [3]. Due to these issues, classical metabolic engineering approaches are oen time consuming, labor intensive, and ineective from an economical standpoint.