2015 Synthetic Biology: Engineering, Evolution & Design (SEED)

Quantitative Metabolic Modeling for Biofuel Production at the Joint Bioenergy Institute

Authors

Hector Garcia Martin - Presenter, Joint BioEnergy Institute (JBEI)
Garrett Birkel, Lawrence Berkeley National Laboratory
Amit Ghosh, Lawrence Berkeley National Laboratory
William Morrell, Sandia National Laboratory
Nathanial Echols, Lawrence Berkeley National Laboratory
Nathan J Hillson, DOE Joint BioEnergy Institute
Paul D. Adams, Joint BioEnergy Institute
Jay D. Keasling, Joint Bioenergy Institute

The goal of the Joint BioEnergy Institute (JBEI) is to produce fundamental scientific discoveries to enable the development of commercially viable processes for large-scale conversion of lignocellulosic biomass into fuels.

The Quantitative Metabolic Modeling (QMM) directorate at the Fuels Synthesis Division is devoted to developing models of metabolism in order to improve biofuel production in a rationally directed fashion. We will describe how the QMM directorate fits in the general JBEI strategy and how we use experimental, computational and mathematical tools to achieve our goal. We will first show how the use of 13C labeling data allows us to effectively constrain metabolic fluxes for genome-scale models and make quantitative predictions. Secondly, we will show how we used quantitative targeted proteomic data to guide metabolic pathway engineering and increase the production titers of limonene, a biofuel molecule. Finally, we will show how new web-based tools for standardized data storage (the Experiment Data Depot, EDD) and interactive flux visualization (Multiomics Visualization Tool, MvT) produce the necessary base to make these predictions possible.