29/11/2011 - Room C209/10 at 14:00 - External Seminar
Synthetic biology addresses problems beyond classical metabolic engineering by importing pathways from other organisms into microbial chassis. The work presented here will focus on the production of therapeutics with the goal of developing an in situ drug delivery device in host cells. The process consists of implementing a heterologous circuit in E. coli by using retrosynthesis, a concept originally developed for synthetic chemistry, which iteratively applies reversed biotransformations (i.e. reversed enzymes-catalyzed reactions) starting from a target product in order to reach precursors that are metabolites endogenous to the host organism. The proposed method is based on the representation of metabolic maps as annotated hypergraphs where substrates, products and reactions are coded into molecular signatures, which are atomic subgraphs contained in molecular structures and reactions. The retrosynthesis method that we have developed in my research group searches for heterologous genes and their associated metabolites through the enumeration and ranking of all feasible pathways going from a source set of metabolites to a desired target compound. Candidate pathways are then ranked to select which pathways are best to engineer. The ranking function is based on several criteria such as inhibitory effects, cytotoxicity of heterologous metabolites, and host compatibility (codon usage, homology). Furthermore, the method is making use of several machine learning based predictive tools developed by our group (the MolSig package) in order to estimate enzyme activity and reaction efficiency at each step of the identified pathways. The retrosynthetic biology approach will be illustrated with the design and experimental implementation of synthetic circuits producing antibacterials in E. coli. Reference: Carbonell P., Planson A.G., Fichera D., Faulon J.L. A retrosynthetic biology approach to metabolic pathway design for therapeutic production. BMC Systems Biology, 2011, 5:122.